Target detection method, device, equipment and storage medium

文档序号:6612 发布日期:2021-09-17 浏览:38次 中文

1. A method of object detection, comprising:

determining distance information and angle information of echo signals in a target detection region, and constructing a distance-angle spectrogram at the same time;

determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram;

determining a gesture type according to the centroid information;

determining a target gesture according to the gesture type, the centroid information, and the gesture angle.

2. The object detection method of claim 1, wherein determining centroid information and a gesture angle of a gesture object from the distance information and the distance-angle spectrogram comprises:

determining centroid information of the gesture target according to the distance information of the echo signal in the target detection region;

determining the gesture angle according to the distance-angle spectrogram and the centroid information.

3. The object detection method of claim 1, further comprising, prior to determining a gesture type from the centroid information:

and determining a centroid variance, a centroid mean value, a centroid variation range, a centroid position angle variance and a centroid position angle variation value according to the centroid information.

4. The object detection method of claim 3, wherein determining a gesture type from the centroid information comprises:

if the centroid variance is smaller than a preset centroid variance, determining that the gesture type is a continuous action; otherwise, determining the gesture type to be a single action.

5. The object detection method according to claim 4, wherein if the gesture type is the single action,

accordingly, determining a target gesture from the gesture type, the centroid information, and the gesture angle comprises:

if the centroid variation range is larger than a preset variation value, the angle variance at the centroid is smaller than a preset angle variance, and the angle variation value is larger than a preset threshold value, determining that the target gesture is a right waving hand;

if the centroid variation range is larger than a preset variation value, the angle variance at the centroid is smaller than a preset angle variance, and the angle variation value is smaller than or equal to a preset threshold value, determining that the target gesture is a left waving hand;

otherwise, determining that the target gesture is a press.

6. The object detection method according to claim 4, wherein if the gesture type is the continuous motion,

accordingly, determining a target gesture from the gesture type, the centroid information, and the gesture angle comprises:

if the centroid mean value is smaller than a preset centroid mean value, determining that the target gesture is hovering in a close range;

otherwise, determining that the target gesture is a long-distance hovering gesture.

7. The object detection method according to claim 5 or 6, further comprising:

and determining a control instruction according to the target gesture, and updating the running state of the target detection equipment loaded with the radar device based on the control instruction.

8. An object detection device, comprising:

the first execution module is used for determining distance information and angle information of echo signals in a target detection area and constructing a distance-angle spectrogram at the same time;

the second execution module is used for determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram;

the gesture type determining module is used for determining a gesture type according to the centroid information;

and the target gesture determination module is used for determining a target gesture according to the gesture type, the centroid information and the gesture angle.

9. An electronic device, characterized in that the device comprises:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement the object detection method of any one of claims 1-7.

10. A storage medium containing computer-executable instructions for performing the object detection method of any one of claims 1-7 when executed by a computer processor.

Background

With the rapid development of information technology, various intelligent devices have gradually entered modern life, and human-machine interaction has become an important part of life. Because the gesture is an important link of communication in human daily life, the gesture recognition is simple, direct and rich in meaning, the gesture recognition is applied to human-computer interaction, the user experience can be greatly enhanced, and the method has wide application prospects. The gesture recognition can help the deaf-mute to normally communicate, automatically drive for assisting, control home work in intelligent home, control multimedia equipment, sightseeing of intelligent museums, virtual reality games and the like, wherein the control of numerous multimedia equipment in daily life is an important application, such as a television, a mobile phone, a sound box, a vehicle-mounted player and the like, can be released from the constraint of a touch screen and keys, liberates two hands and realizes intelligent human-computer interaction.

In the prior art, gesture recognition can be performed based on vision, and the vision recognition can realize recognition of various gestures and has high recognition accuracy. However, the visual recognition needs to acquire a high-resolution image, the data volume of the image is large, it takes a long time to process the image, the visual recognition equipment has a limited visual range, the sight line is easily blocked, and the influence of the light intensity is easy, so that the privacy is violated, and the like.

Therefore, a target detection method is needed, which does not need to collect and process high-resolution images to realize gesture recognition, and has the advantages of small data processing amount and quick and simple operation.

Disclosure of Invention

The invention provides a target detection method, a target detection device, target detection equipment and a storage medium, which are used for realizing gesture recognition without acquiring and processing high-resolution images and improving the target detection rate.

In a first aspect, an embodiment of the present invention provides a target detection method, including:

determining distance information and angle information of echo signals in a target detection region, and constructing a distance-angle spectrogram at the same time;

determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram;

determining a gesture type according to the centroid information;

determining a target gesture according to the gesture type, the centroid information, and the gesture angle.

The embodiment of the invention provides a target detection method, which comprises the following steps: determining distance information and angle information of echo signals in a target detection region, and constructing a distance-angle spectrogram at the same time; determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram; determining a gesture type according to the centroid information; determining a target gesture according to the gesture type, the centroid information, and the gesture angle. According to the technical scheme, the centroid information and the gesture angle of the gesture target in the target detection area can be determined according to the distance information and the angle information of the echo signal in the target detection area, the gesture type of the gesture target can be determined according to the centroid information, the gesture type, the centroid information and the gesture angle can be combined to determine the target gesture, the gesture recognition is achieved without collecting and processing high-resolution images, the data volume required to be processed is small, and the target detection rate is improved.

Further, determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram, comprising:

determining centroid information of the gesture target according to the distance information of the echo signal in the target detection region;

determining the gesture angle according to the distance-angle spectrogram and the centroid information.

Further, before determining the gesture type according to the centroid information, the method further includes:

and determining a centroid variance, a centroid mean value, a centroid variation range, a centroid position angle variance and a centroid position angle variation value according to the centroid information.

Further, determining a gesture type according to the centroid information includes:

if the centroid variance is smaller than a preset centroid variance, determining that the gesture type is a continuous action; otherwise, determining the gesture type to be a single action.

Further, if the gesture type is the single action,

accordingly, determining a target gesture from the gesture type, the centroid information, and the gesture angle comprises:

if the centroid variation range is larger than a preset variation value, the angle variance at the centroid is smaller than a preset angle variance, and the angle variation value is larger than a preset threshold value, determining that the target gesture is a right waving hand;

if the centroid variation range is larger than a preset variation value, the angle variance at the centroid is smaller than a preset angle variance, and the angle variation value is smaller than or equal to a preset threshold value, determining that the target gesture is a left waving hand;

otherwise, determining that the target gesture is a press.

Further, if the gesture type is the continuous motion,

accordingly, determining a target gesture from the gesture type, the centroid information, and the gesture angle comprises:

if the centroid mean value is smaller than a preset centroid mean value, determining that the target gesture is hovering in a close range;

otherwise, determining that the target gesture is a long-distance hovering gesture.

Further, still include:

and determining a control instruction according to the target gesture, and updating the running state of the target detection equipment loaded with the radar device based on the control instruction.

In a second aspect, an embodiment of the present invention further provides an object detection apparatus, including:

the first execution module is used for determining distance information and angle information of echo signals in a target detection area and constructing a distance-angle spectrogram at the same time;

the second execution module is used for determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram;

the gesture type determining module is used for determining a gesture type according to the centroid information;

and the target gesture determination module is used for determining a target gesture according to the gesture type, the centroid information and the gesture angle.

In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement the object detection method as described in any one of the first aspects.

In a fourth aspect, a storage medium contains computer-executable instructions for performing the object detection method as described in any one of the first aspects when executed by a computer processor.

In a fifth aspect, the present application provides a computer program product comprising computer instructions which, when run on a computer, cause the computer to perform the object detection method as provided in the first aspect.

It should be noted that all or part of the computer instructions may be stored on the computer readable storage medium. The computer-readable storage medium may be packaged with a processor of the target detection apparatus, or may be packaged separately from the processor of the target detection apparatus, which is not limited in this application.

For the descriptions of the second, third, fourth and fifth aspects in this application, reference may be made to the detailed description of the first aspect; in addition, for the beneficial effects described in the second aspect, the third aspect, the fourth aspect and the fifth aspect, reference may be made to the beneficial effect analysis of the first aspect, and details are not repeated here.

In the present application, the names of the above-mentioned object detection devices do not limit the devices or functional modules themselves, and in actual implementation, the devices or functional modules may appear by other names. Insofar as the functions of the respective devices or functional modules are similar to those of the present application, they fall within the scope of the claims of the present application and their equivalents.

These and other aspects of the present application will be more readily apparent from the following description.

Drawings

Fig. 1 is a flowchart of a target detection method according to an embodiment of the present invention;

fig. 2 is a flowchart of a target detection method according to a second embodiment of the present invention;

fig. 3 is a flowchart of determining a target gesture in a target detection method according to a second embodiment of the present invention;

fig. 4 is a flowchart of determining a target gesture in another target detection method according to a second embodiment of the present invention;

fig. 5 is a schematic structural diagram of a target detection apparatus according to a third embodiment of the present invention;

fig. 6 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.

Detailed Description

The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.

The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone.

The terms "first" and "second" and the like in the description and drawings of the present application are used for distinguishing different objects or for distinguishing different processes for the same object, and are not used for describing a specific order of the objects.

Furthermore, the terms "including" and "having," and any variations thereof, as referred to in the description of the present application, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like. In addition, the embodiments and features of the embodiments in the present invention may be combined with each other without conflict.

It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.

In the description of the present application, the meaning of "a plurality" means two or more unless otherwise specified.

Example one

Fig. 1 is a flowchart of a target detection method according to an embodiment of the present invention, where this embodiment is applicable to a case where gesture recognition is implemented without acquiring and processing a high-resolution image, and the method may be executed by a target detection device, and specifically includes the following steps:

and step 110, determining distance information and angle information of echo signals in the target detection region, and constructing a distance-angle spectrogram.

The target detection area can be a position area within a preset distance of the front side of the radar device, the preset distance is not specifically limited, and the target detection area can be determined according to actual requirements. In the embodiment of the present invention, the preset distance may be the first N distance units, the target detection may be performed based on the first N distance units, and other targets and actions exceeding the target detection area may be regarded as invalid targets. The radar device can include transmitting antenna and receiving antenna, and transmitting antenna can send the electromagnetic wave signal of frequency modulation continuous wave form to current environment in, can send to in the target detection region certainly, and the object in the target detection region can carry out the scattering to the electromagnetic wave signal and obtains the scattering echo, and receiving antenna can receive aforementioned scattering echo, further obtains echo signal.

Specifically, the gesture in the target detection region may scatter an electromagnetic wave signal sent by the transmitting antenna to obtain a scattering echo, and the receiving antenna may receive the scattering echo to further obtain an echo signal. The echo signal can be a three-dimensional data cubic signal of a fast time dimension, a slow time dimension and an antenna dimension.

The receiving antenna can send the echo signal to the server after receiving the echo signal, and the server can perform fast fourier transform on the echo signal based on a single frequency (chirp) to extract the range information r [ n ] of the echo signal, wherein n represents a range unit.

Furthermore, angle information can be determined based on a super-resolution angle estimation method, and a distance-angle spectrogram M [ v, n ] is obtained, wherein v represents an angle value, and n represents a distance unit. The super-resolution angle estimation method may include a Multiple Signal Classification (MUSIC) algorithm.

Taking the MUSIC algorithm as an example for explanation, firstly, a covariance matrix of an echo signal can be constructed according to distance information, then eigenvalue decomposition is performed on the covariance matrix, a signal subspace eigenvector matrix, a signal subspace eigenvalue matrix, a noise subspace eigenvector matrix and a noise subspace eigenvalue matrix are obtained, the number of signal sources can be determined according to the eigenvalues of the covariance matrix, a distance-angle spectrogram is determined according to a signal subspace, a noise subspace and a steering vector of the echo signal, meanwhile, a parameter range peak value of the echo signal can be searched, and an angle corresponding to a maximum value point of the distance information is determined as angle information corresponding to the distance information, namely, an incidence direction of the echo signal corresponding to the distance information. It should be noted that the number of signal sources may be two. Specifically, a covariance matrix of the echo signal can be constructed according to the formula (1), eigenvalue decomposition is performed on the covariance matrix according to the formula (2), and a distance-angle spectrogram is determined according to the formula (3):

wherein R iskk,rFor the constructed signal covariance matrix, N is the number of fixed signal sources, UsFor a signal subspace eigenvector matrix, sigmasFor a matrix of signal subspace eigenvalues, UmFor a noisy subspace eigenvector matrix, sigmamIs a noise subspace eigenvalue matrix. Alpha (theta) is a steering vector of an array element of an echo signal, PmusicIs the determined distance-angle spectrogram.

In the embodiment of the invention, the distance information r [ n ] of the echo signal is extracted based on a single chirp, the data calculation amount is less, and the calculation efficiency can be improved.

After the receiving antenna sends the echo signal to the server, the server may amplify and mix the echo signal, and may obtain the echo signal based on sampling of an Analog-to-Digital Converter (ADC). The scattered echoes may be signal amplified and signal mixed based on low noise amplifiers and mixers.

It should be further noted that the embodiment of the present invention has low computational complexity, and can determine distance information and angle information of an echo signal in a target detection region based on a microprocessor (Advanced RISC Machines, ARM), and construct a distance-angle spectrogram at the same time, thereby further implementing embedded device transplantation and edge computation.

And 120, determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram.

In the embodiment of the invention, whether a target exists at each position in the target detection area can be determined based on the distance threshold, if the distance information is greater than the distance threshold, the position can be determined as the target position and the target exists, and the distance information of the position can be determined according to the echo signal; otherwise, it may be determined that the location is a non-target location and no target exists, the distance information of the location may be set to 0. The processed distance information may be determined as r' n.

Specifically, the centroid information of the gesture target may be a weighted average of the position of the gesture target and the corresponding amplitude thereof, and specifically, the centroid information may be determined according to formula (4):

where N represents the number of range cells.

Further, after determining the centroid information, a position of the centroid information may be determined in the distance-angle spectrogram, an angle value θ with a maximum spectral value in the angle spectrogram is found near a position corresponding to the centroid information, and the angle value θ with the maximum spectral value is determined as a gesture angle, and specifically, the gesture angle may be determined according to formula (5):

where v represents the angle value and Q represents the distance unit.

And step 130, determining the gesture type according to the centroid information.

Wherein, the variance of the centroid information can be determined according to the centroid information to obtain the centroid variance dvar. Specifically, the variance of the centroid information in the current sliding window can be calculated to obtain dvar,dvarStatistical features of the gesture target distance dimensional stability may be reflected. The current sliding window may be determined according to actual requirements, which is not specifically limited herein, and in the embodiment of the present invention, the length of the sliding window may be set to 0.6 second.

Specifically, the single frame detection may be performed on the target detection area multiple times, each time the centroid variance is determined, and the centroid variance is compared with the preset centroid variance multiple times, if the centroid variance is less than the preset centroid variance, the gesture type may be determined as a continuous action, and if the centroid variance is greater than or equal to the preset centroid variance, the gesture type may be determined as a single action.

In the embodiment of the present invention, the preset centroid variance may be 0.1.

Step 140, determining a target gesture according to the gesture type, the centroid information and the gesture angle.

Further, the mean value of the centroid can be determined according to the centroid information to obtain a centroid mean value dmean(ii) a Specifically, the mean value of the centroid in the current sliding window can be calculated to obtain dmean,dmeanThe location characteristics of the gesture target may be reflected. The variation range d of the centroid can be determined according to the centroid informationspan(ii) a Specifically, the difference between the farthest distance information and the nearest distance information in the gesture target may be calculated to obtain dspan,dspanThe magnitude of the change in the gesture target distance dimension may be reflected. The angle variance at the position of the centroid can be determined according to the gesture angle, and the angle variance theta is obtainedvar(ii) a The variance theta of the angle of the gesture target can be specifically calculatedvar,θvarCan reflect the stability of the gesture target in the angle dimensionAnd (5) qualitative statistical characteristics. The change value theta of the angle can be determined according to the gesture anglediffSpecifically, the difference θ between the ending angle and the starting angle may be calculateddiff,θdiffThe direction of motion of the gesture target may be reflected.

Specifically, if the gesture type is a continuous motion, the centroid mean value and the preset centroid mean value may be compared, if the centroid mean value is smaller than the preset centroid mean value, the target gesture is determined to be hovering in a close distance, and if the centroid mean value is greater than or equal to the preset centroid mean value, the target gesture is determined to be hovering in a long distance. If the gesture type is a single action, comparing the centroid variation range with a preset variation value and comparing the angle variance with a preset angle variance, and if the centroid variation range and the angle variance do not meet the condition that the centroid variation range is larger than the preset variation value and the angle variance is smaller than the preset angle variance, determining that the target gesture is pressing; if the centroid variation range is larger than a preset variation value, the angle variance is smaller than a preset angle variance, and the angle variation value is larger than a preset threshold value, determining that the target gesture is a right waving hand; and if the centroid variation range is larger than the preset range, the angle variance is smaller than the preset angle variance, and the angle variation value is smaller than or equal to the preset threshold value, determining that the target gesture is a left waving hand.

In the embodiment of the invention, when no gesture target is detected in the target detection area, the target detection state can be determined to be an idle state, and only target detection is carried out in the idle state; when a single-frame gesture target is detected in the target detection area, the target detection state can be determined as an activated state, the gesture target is continuously detected in the activated state, the centroid information and the gesture angle are determined according to the gesture target, and the statistical characteristics are calculated; in the activated state, if the gesture target is not detected by single-frame detection, the target detection state can be determined as a waiting ending state, multi-frame detection is continued until the gesture target is not detected by multi-frame detection, the target detection state can be determined as an ending state, target gestures are determined and output, and centroid information and the gesture target are reset in the next frame.

The target detection method provided by the embodiment of the invention determines the distance information and the angle information of the echo signal in the target detection area, and simultaneously constructs a distance-angle spectrogram; determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram; determining a gesture type according to the centroid information; determining a target gesture according to the gesture type, the centroid information, and the gesture angle. According to the technical scheme, the centroid information and the gesture angle of the gesture target in the target detection area can be determined according to the distance information and the angle information of the echo signal in the target detection area, the gesture type of the gesture target can be determined according to the centroid information, the gesture type, the centroid information and the gesture angle can be combined to determine the target gesture, the gesture recognition is achieved without collecting and processing high-resolution images, the data volume required to be processed is small, and the target detection rate is improved.

Example two

Fig. 2 is a flowchart of a target detection method according to a second embodiment of the present invention, which is embodied on the basis of the second embodiment. In this embodiment, the method may further include:

step 210, determining distance information and angle information of echo signals in the target detection region, and constructing a distance-angle spectrogram.

In the embodiment of the invention, before the distance information and the angle information of the echo signal in the target detection area are determined, distance dimension clutter suppression can be performed on the echo signal of a single chirp, and the distance dimension clutter suppression can be specifically performed on the basis of band-pass filtering, mean filtering, adaptive iterative filtering and the like. Taking adaptive iterative filtering as an example, distance dimension clutter suppression can be performed according to equations (6) and (7):

yk[n]=rk[n]-ck[n] (6)

ck+1[n]=αck[n]+(1-α)rk[n] (7)

wherein r isk[n]Representing the signal after a fast Fourier transform of the echo signal of a single chirp based on the distance dimension, yk[n]Representing the result after clutter subtractionFiltered data, ck[n]Representing a clutter map of the current frame. Alpha is more than or equal to 0 and less than or equal to 1, and the update coefficient of the clutter map is represented.

And further detecting the echo signals in the target detection area, and regarding other targets and actions exceeding the target detection area as invalid targets. Of course, whether a target exists at each position in the target detection area may be determined based on the distance threshold, and if the distance information is greater than the distance threshold, it may be determined that the position is the target position and the target exists at the position, and the distance information of the position may be determined according to the echo signal; otherwise, it may be determined that the location is a non-target location and no target exists, the distance information of the location may be set to 0. The processed distance information may be determined as y' n.

And step 220, determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram.

In one embodiment, step 220 may specifically include:

determining centroid information of the gesture target according to the distance information of the echo signal in the target detection region; determining the gesture angle according to the distance-angle spectrogram and the centroid information.

Specifically, the centroid information of the gesture target may be a weighted average of the position of the gesture target and the corresponding amplitude thereof, and specifically, the centroid information may be determined according to formula (8):

where N represents the number of range cells.

Further, after determining the centroid information, a position of the centroid information may be determined in the distance-angle spectrogram, an angle value θ with a maximum spectral value in the angle spectrogram is found near a position corresponding to the centroid information, and the angle value θ with the maximum spectral value is determined as a gesture angle, and specifically, the gesture angle may be determined according to formula (9):

where v denotes an angle value and P denotes a distance unit.

And step 230, determining a centroid variance, a centroid mean, a centroid variation range, a centroid angle variance and a centroid angle variation value according to the centroid information.

Specifically, as described in the first embodiment, the variance of the centroid information may be determined according to the centroid information, and the centroid variance d is obtainedvarDetermining the mean value of the mass center according to the mass center information to obtain a mass center mean value dmeanDetermining the variation range d of the centroid according to the centroid informationspan. The angle variance at the position of the centroid can be determined according to the gesture angle, and the angle variance theta is obtainedvarDetermining a change value theta of the angle according to the gesture anglediff

And 240, determining the gesture type according to the centroid information.

In one embodiment, step 240 may specifically include:

if the centroid variance is smaller than a preset centroid variance, determining that the gesture type is a continuous action; otherwise, determining the gesture type to be a single action.

As described in the previous embodiment, the preset centroid variance may be 0.1.

Step 250, determining a target gesture according to the gesture type, the centroid information and the gesture angle.

In one embodiment, if the gesture type is the single motion, step 250 may specifically include:

if the centroid variation range is larger than a preset variation value, the angle variance at the centroid is smaller than a preset angle variance, and the angle variation value is larger than a preset threshold value, determining that the target gesture is a right waving hand; if the centroid variation range is larger than a preset variation value, the angle variance at the centroid is smaller than a preset angle variance, and the angle variation value is smaller than or equal to a preset threshold value, determining that the target gesture is a left waving hand; otherwise, determining that the target gesture is a press.

Fig. 3 is a flowchart of determining a target gesture in a target detection method according to a second embodiment of the present invention, as shown in fig. 3, specifically, the centroid variation range and the preset variation value, and the angle variance and the preset angle variance may be compared in the ending state, and if the centroid variation range and the angle variance do not satisfy that the centroid variation range is greater than the preset variation value and the angle variance is smaller than the preset angle variance, the target gesture is determined to be a press; if the centroid variation range is larger than a preset variation value, the angle variance is smaller than a preset angle variance, and the angle variation value is larger than a preset threshold value, determining that the target gesture is a right waving hand; and if the centroid variation range is larger than the preset range, the angle variance is smaller than the preset angle variance, and the angle variation value is smaller than or equal to the preset threshold value, determining that the target gesture is a left waving hand.

It should be noted that the preset variation value, the preset angle variance and the preset threshold may be set according to actual requirements, in the embodiment of the present invention, the preset variation value may be 3, the preset angle variance may be 50, and the preset threshold may be 0.

In one embodiment, if the gesture type is the continuous motion, step 250 may specifically include:

if the centroid mean value is smaller than a preset centroid mean value, determining that the target gesture is hovering in a close range; otherwise, determining that the target gesture is a long-distance hovering gesture.

Fig. 4 is a flowchart of determining a target gesture in another target detection method provided in the second embodiment of the present invention, as shown in fig. 4, specifically, in the active state, the centroid mean value and the preset centroid mean value may be compared, if the centroid mean value is smaller than the preset centroid mean value, the target gesture is determined to be hovering in a close distance, and if the centroid mean value is greater than or equal to the preset centroid mean value, the target gesture is determined to be hovering in a long distance.

It should be noted that the preset centroid mean value may be set according to actual requirements, and in the embodiment of the present invention, the preset centroid mean value may be 6.

And step 260, determining a control instruction according to the target gesture, and updating the running state of the target detection equipment loaded with the radar device based on the control instruction.

The target detection device may be configured to control a basic playing function of the multimedia device based on the control instruction, and the multimedia device may include a music player. The basic play functions controlled by the control commands may include a previous song, a next song, start/pause play, volume increase, and volume decrease, and the control commands corresponding to the target gestures may be determined based on the basic play functions and the corresponding table of target gestures and control commands shown in table 1.

Specifically, all target gestures may be designed with corresponding significances of actions according to the control instruction, and in the gesture operation process, a person may face the radar device. The right hand waving gesture can wave a hand from the left side to the right side corresponding to the palm, a right page turning action of the touch screen is simulated, and the corresponding control instruction can be a next song; the left hand waving gesture can wave a hand from the right to the left corresponding to the palm, a left page turning action of the touch screen is simulated, and the corresponding control instruction can be a previous song; the pressing gesture can correspondingly extend out of the palm, the action of pressing the switch button is simulated towards the direction of the radar device, then the action is retracted, and the corresponding control instruction can be play starting/pausing; the short-distance hovering gesture can correspondingly extend out of the palm and hover at a position relatively close to the radar to simulate a continuous volume-pressing action, and the corresponding control instruction can be volume reduction; the remote hovering gesture can correspondingly extend out of the palm and hover at a position relatively far away from the radar, the action of continuously pressing the volume and the key is simulated, and the corresponding control instruction can be used for increasing the volume. The first three target gestures can be single actions, and judgment is made when each action is finished; the last two target gestures can be continuous actions, and continuous judgment is carried out according to set time intervals. Additionally, the time of hover may determine the volume increase as well as the volume decrease.

TABLE 1 target gesture and control instruction correspondence table

The second target detection method provided by the embodiment of the invention determines the distance information and the angle information of the echo signal in the target detection area, and simultaneously constructs a distance-angle spectrogram; determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram; determining a gesture type according to the centroid information; determining a target gesture according to the gesture type, the centroid information, and the gesture angle. According to the technical scheme, the centroid information and the gesture angle of the gesture target in the target detection area can be determined according to the distance information and the angle information of the echo signal in the target detection area, the gesture type of the gesture target can be determined according to the centroid information, the gesture type, the centroid information and the gesture angle can be combined to determine the target gesture, the gesture recognition is achieved without collecting and processing high-resolution images, the data volume required to be processed is small, and the target detection rate is improved.

The target detection method provided by the embodiment of the invention has the non-contact characteristic, can get rid of the constraint of a touch screen and a key, is not influenced by light, can work all day long, does not damage personal privacy, and is simple, low in complexity and effective.

In addition, the control instruction can be determined according to the target gesture, the running state of the target detection equipment loaded with the radar device is updated based on the control instruction, the control over the target detection equipment is achieved, the playing control over the multimedia equipment is further achieved, the designed target gesture is natural, accords with the corresponding operation instruction, has the corresponding simulation operation, and can improve the user experience.

EXAMPLE III

Fig. 5 is a structural diagram of a target detection device according to a third embodiment of the present invention, where the device may be applied to a case where gesture recognition is implemented without acquiring and processing a high-resolution image, so as to improve a target detection rate. The apparatus may be implemented in software and/or hardware and is typically integrated in an object detection device, such as a computer.

As shown in fig. 5, the apparatus includes:

a first execution module 510, configured to determine distance information and angle information of an echo signal in a target detection region, and construct a distance-angle spectrogram at the same time;

a second executing module 520, configured to determine centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram;

a gesture type determining module 530 for determining a gesture type according to the centroid information;

a target gesture determination module 540, configured to determine a target gesture according to the gesture type, the centroid information, and the gesture angle.

The target detection device provided by the embodiment determines distance information and angle information of an echo signal in a target detection area, and simultaneously constructs a distance-angle spectrogram; determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram; determining a gesture type according to the centroid information; determining a target gesture according to the gesture type, the centroid information, and the gesture angle. According to the technical scheme, the centroid information and the gesture angle of the gesture target in the target detection area can be determined according to the distance information and the angle information of the echo signal in the target detection area, the gesture type of the gesture target can be determined according to the centroid information, the gesture type, the centroid information and the gesture angle can be combined to determine the target gesture, the gesture recognition is achieved without collecting and processing high-resolution images, the data volume required to be processed is small, and the target detection rate is improved.

On the basis of the foregoing embodiment, the first executing module 510 is specifically configured to:

determining distance information and angle information of echo signals in a target detection region, and constructing a distance-angle spectrogram at the same time;

determining centroid information of the gesture target according to the distance information of the echo signal in the target detection region;

determining the gesture angle according to the distance-angle spectrogram and the centroid information.

On the basis of the above embodiment, the apparatus further includes:

and the third execution module is used for determining the centroid variance, the centroid mean value, the centroid variation range, the centroid angle variance and the centroid angle variation value according to the centroid information.

On the basis of the foregoing embodiment, the gesture type determining module 530 is specifically configured to:

if the centroid variance is smaller than a preset centroid variance, determining that the gesture type is a continuous action; otherwise, determining the gesture type to be a single action.

On the basis of the foregoing embodiment, if the gesture type is the single action, accordingly, the target gesture determining module 540 is specifically configured to:

if the centroid variation range is larger than a preset variation value, the angle variance at the centroid is smaller than a preset angle variance, and the angle variation value is larger than a preset threshold value, determining that the target gesture is a right waving hand;

if the centroid variation range is larger than a preset variation value, the angle variance at the centroid is smaller than a preset angle variance, and the angle variation value is smaller than or equal to a preset threshold value, determining that the target gesture is a left waving hand;

otherwise, determining that the target gesture is a press.

On the basis of the foregoing embodiment, if the gesture type is the continuous motion, accordingly, the target gesture determining module 540 is specifically configured to:

if the centroid mean value is smaller than a preset centroid mean value, determining that the target gesture is hovering in a close range;

otherwise, determining that the target gesture is a long-distance hovering gesture.

On the basis of the above embodiment, the apparatus further includes:

and the control module is used for determining a control instruction according to the target gesture and updating the running state of the target detection equipment loaded with the radar device based on the control instruction.

The target detection device provided by the embodiment of the invention can execute the target detection method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.

Example four

Fig. 6 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention, and fig. 6 shows a block diagram of an exemplary electronic device 7 suitable for implementing the embodiment of the present invention. The electronic device 7 shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiment of the present invention.

As shown in fig. 6, the electronic device 7 is in the form of a general purpose computing electronic device. The components of the electronic device 7 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.

Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

The electronic device 7 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by electronic device 7 and includes both volatile and nonvolatile media, removable and non-removable media.

The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. The electronic device 7 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, and commonly referred to as a "hard drive"). Although not shown in FIG. 6, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.

A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.

Electronic device 7 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with electronic device 7, and/or with any devices (e.g., network card, modem, etc.) that enable electronic device 7 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, the electronic device 7 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 20. As shown in fig. 6, the network adapter 20 communicates with other modules of the electronic device 7 via the bus 18. It should be appreciated that although not shown in FIG. 6, other hardware and/or software modules may be used in conjunction with electronic device 7, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

The processing unit 16 executes various functional applications and page displays, such as implementing the object detection method provided by the present embodiment,

wherein, the method comprises the following steps:

determining distance information and angle information of echo signals in a target detection region, and constructing a distance-angle spectrogram at the same time;

determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram;

determining a gesture type according to the centroid information;

determining a target gesture according to the gesture type, the centroid information, and the gesture angle.

Of course, those skilled in the art can understand that the processor can also implement the technical solution of the target detection method provided in any embodiment of the present invention.

EXAMPLE five

An embodiment five of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements, for example, an object detection method provided in the embodiment, where the method includes:

determining distance information and angle information of echo signals in a target detection region, and constructing a distance-angle spectrogram at the same time;

determining centroid information and a gesture angle of the gesture target according to the distance information and the distance-angle spectrogram;

determining a gesture type according to the centroid information;

determining a target gesture according to the gesture type, the centroid information, and the gesture angle.

Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer-readable storage medium may be, for example but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

It will be understood by those skilled in the art that the modules or steps of the invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and optionally they may be implemented by program code executable by a computing device, such that it may be stored in a memory device and executed by a computing device, or it may be separately fabricated into various integrated circuit modules, or it may be fabricated by fabricating a plurality of modules or steps thereof into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments illustrated herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

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