Action detection method, system, apparatus and computer readable storage medium

Abstract

The application provides a motion detection method, system and device and a computer readable storage medium. The method comprises the steps of continuously acquiring channel impulse response data collected by an ultra-wideband radar; determining a direction and speed feature corresponding to the channel impulse response data; determining a motion feature of a target object according to the direction and speed feature; and matching a target motion corresponding to the motion feature. The direction and speed feature of the target object in a detection area is determined by setting the ultra-wideband radar, so that the motion feature of the target object in the detection area can be recognized, the motion of the target object in the detection area is reflected, and then the corresponding target motion is matched based on the motion, so that the detection can be realized based on the actual motion characteristics of the kicking motion, and the detection accuracy is improved.

Description

Technical Field

[0001] This invention relates to the field of vehicles, and more particularly to a motion detection method, system, device, and computer-readable storage medium. Background Technology

[0002] With the trend of automotive intelligence, intelligent tailgate opening has become a common and important requirement. When users are carrying heavy items and cannot free their hands, the foot-operated tailgate function allows users to control the tailgate opening with leg movements, which is extremely convenient.

[0003] In the prior art, the detection of kicking motions used to control the tailgate function is usually achieved by distance detection, such as capacitance detection. However, the environment in which vehicles are used is complex, and this method is easily affected by environmental factors, resulting in low accuracy in detecting kicking motions. Summary of the Invention

[0004] The main objective of one embodiment of the present invention is to provide a motion detection method, system, device, and computer-readable storage medium, which aims to solve the problem of low detection accuracy of kicking motion in the prior art.

[0005] An embodiment of the present invention provides an action detection method, the method comprising the steps of: Continuously acquire channel impulse response data collected by ultra-wideband radar; Determine the directional velocity characteristics corresponding to the channel impulse response data; The motion characteristics of the target object are determined based on the directional velocity characteristics; Match the target action corresponding to the motion feature.

[0006] Optionally, determining the directional velocity characteristics corresponding to the channel impulse response data includes: Determine the signal phase change rate of the channel impulse response data, and determine the object orientation corresponding to the channel impulse response data; Match the signal frequency shift corresponding to the rate of change of the signal phase; Obtain the signal wavelength corresponding to the channel impulse response data, and calculate the object velocity based on the signal wavelength and the signal frequency shift; The directional velocity feature is obtained by associating the object's velocity with the object's direction.

[0007] Optionally, determining the object direction corresponding to the channel impulse response data includes: Wavelet analysis is performed on the channel impulse response data to obtain the positive and negative signal energies; If the positive signal energy is greater than the first energy threshold, then the direction of the object is determined to be away from the ultra-wideband radar, wherein the first energy threshold is a positive number; If the negative signal energy is less than the second energy threshold, then the direction of the object is determined to be close to the ultra-wideband radar, wherein the second energy threshold is a negative number.

[0008] Optionally, determining the signal phase change rate of the channel impulse response data includes: The signal energy is obtained by wavelet analysis of the channel impulse response data within the current noise detection period; The signal energy is converted into signal decibels, and the average signal decibels within the current noise detection period are calculated; Obtain the historical noise decibel level of the previous noise detection cycle, and combine the average signal decibel level with the historical noise decibel level to obtain the noise decibel level of the current cycle; The target signal is obtained by subtracting the current period noise level from the average signal level in decibels. Determine the rate of change of the target signal's phase.

[0009] Optionally, determining the signal phase change rate of the target signal includes: The maximum frequency signal corresponding to each moment in the target signal is retained, and the target frequency signal is obtained by combining the maximum frequency signals corresponding to each moment. Determine the rate of change of the signal phase corresponding to the target frequency signal.

[0010] Optionally, the directional velocity feature includes the object direction and the object velocity; determining the motion feature of the target object based on the directional velocity feature includes: Identify multiple directional velocity features that are continuous, have the same direction, and have a velocity greater than a preset velocity threshold. Determine whether the duration of the multiple directional velocity features is greater than a preset time threshold. If the duration of multiple directional velocity features is greater than the preset time threshold, then the detected motion feature is determined to be a unidirectional movement feature, wherein the direction of the unidirectional movement feature is the object direction corresponding to the multiple directional velocity features.

[0011] Optionally, the matching of the target action corresponding to the motion feature includes: Obtain a plurality of continuously defined motion features; The motion features are arranged according to the detection order of the motion features; In the preset kicking motion, a matching kicking motion is matched with a preset feature arrangement that is consistent with the motion feature arrangement; The matching kicking motion is taken as the target motion.

[0012] Optionally, the step of obtaining the motion feature arrangement based on the detection order of the motion features includes: Obtain the motion cycle features of the motion feature arrangement; Determine whether the action cycle characteristics meet the action recognition conditions; If the motion cycle feature satisfies the motion recognition condition, then the matching kicking motion is arranged and matched based on the motion feature.

[0013] Optionally, determining whether the action cycle feature satisfies the action recognition condition includes: Obtain the maximum speed, maximum acceleration, and cycle duration from the action cycle characteristics; Determine whether the maximum speed is within a preset speed range, whether the maximum acceleration is greater than a preset acceleration threshold, and whether the period duration is less than a preset duration threshold; If the maximum speed is within a preset speed range, the maximum acceleration is greater than a preset acceleration threshold, and the period duration is less than a preset duration threshold, then the action recognition condition is met.

[0014] Embodiments of the present invention also provide a motion detection system, including a processor and a memory connected to the processor, wherein the memory stores program code for a data acquisition module, program code for a direction and velocity feature module, program code for a motion feature module, and program code for a matching module. The processor is configured to execute the data acquisition module program code to continuously acquire channel impulse response data collected by the ultra-wideband radar; The processor is also configured to execute directional velocity feature module code to determine the directional velocity features corresponding to the channel impulse response data; The processor is also configured to execute motion feature module code to determine the motion features of the target object based on the directional velocity features; The processor is also configured to execute matching module code to match the target action corresponding to the motion feature.

[0015] An embodiment of the present invention also provides an action detection device, the action detection device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the action detection method as described above.

[0016] Embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the action detection method described above.

[0017] This invention provides an action detection method, system, device, and computer-readable storage medium that continuously acquires channel impulse response data collected by an ultra-wideband radar; determines the directional velocity characteristics corresponding to the channel impulse response data; determines the motion characteristics of a target object based on the directional velocity characteristics; and matches the target action corresponding to the motion characteristics. By using an ultra-wideband radar to determine the directional velocity characteristics of a target object within the detection area, the motion characteristics of the target object in the detection area can be identified, reflecting the motion of the target object within the detection area. Furthermore, based on the motion, the corresponding target action can be matched, enabling detection based on the actual motion characteristics of a kicking motion, thus improving detection accuracy. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the first embodiment of the motion detection method of the present invention; Figure 2 This is a schematic diagram of the ultra-wideband radar setup for the motion detection method according to an embodiment of the present invention; Figure 3 This is a detailed flowchart of the motion detection method in an embodiment of the present invention; Figure 4 This is a detailed flowchart of the object velocity calculation in the motion detection method of this invention. Figure 5 This is a schematic diagram of the maximum frequency signal filtering method for motion detection in an embodiment of the present invention; Figure 6 This is a schematic diagram of a vertical kick scenario using the motion detection method according to an embodiment of the present invention; Figure 7 This is a schematic diagram of a side kick scenario using the motion detection method of this invention. Figure 8 This is a schematic diagram of the module structure of the motion detection device according to an embodiment of the present invention. Detailed Implementation

[0021] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0022] This invention provides an action detection method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the motion detection method of the present invention. The method includes the following steps: Step S10: Continuously acquire channel impulse response data collected by the ultra-wideband radar; UWB (Ultra Wide Band) radar is a radar device based on UWB technology.

[0023] CIR (Channel Impulse Response) indicates the signal strength reflected back after a signal emitted by an ultra-wideband radar travels through different distances. Channel impulse response data reflects the environmental characteristics of the ultra-wideband radar and is usually represented by an array. The values ​​at different positions in the array represent the reflection intensity of the radar's emitted signal at different distances.

[0024] The ultra-wideband radar is installed at the rear of the vehicle. The specific location can be determined based on actual needs, such as installing it under the chassis at the rear of the vehicle. The detection area of ​​the ultra-wideband radar can include a certain area outside the rear of the vehicle and a certain area under the rear chassis, as shown in [reference needed]. Figure 2 The detection area of ​​the ultra-wideband radar is defined by a fan-shaped area pointing towards the rear of the vehicle, with the ultra-wideband radar as the apex.

[0025] Step S20: Determine the directional velocity characteristics corresponding to the channel impulse response data; Directional velocity characteristics are the features of directional movement relative to the ultra-wideband radar, as indicated by channel impulse response data; specifically, they can include the direction and speed of movement of the target object relative to the ultra-wideband radar.

[0026] As the Doppler effect describes, when there is relative motion between a wave source and an observer, the frequency of the wave received by the observer deviates from the actual frequency of the wave source. In this embodiment, the ultra-wideband radar is the observer, and the target object within the detection area reflects the signal emitted by the ultra-wideband radar, making the target object the wave source. The movement between the target object and the ultra-wideband radar causes a change in the frequency of the signal received by the ultra-wideband radar, i.e., the channel impulse response data also changes. Therefore, the channel impulse response data can reflect the relative motion relationship between the target object and the ultra-wideband radar. When motion detection is required, the vehicle is stationary, i.e., the ultra-wideband radar is stationary. Therefore, the relative motion directly reflects the motion of the target object. Thus, the channel impulse response data can be used to determine the directional movement characteristics of the target object relative to the ultra-wideband radar.

[0027] Step S30: Determine the motion characteristics of the target object based on the directional velocity characteristics; Directional velocity characteristics reflect the relative motion of the target object with respect to the ultra-wideband radar, while the ultra-wideband radar is stationary. Therefore, directional velocity characteristics can determine the motion of the target object itself, i.e., motion characteristics.

[0028] Motion characteristics indicate the type of motion of the target object, such as kicking, retracting the leg, or side kicking.

[0029] Step S40: Match the target action corresponding to the motion features.

[0030] The action refers to the relevant action set in the vehicle to trigger vehicle control; vehicle control includes tailgate control, front trunk control, etc.; the specific type of action can be preset by the factory or set by the user; actions include kicking actions, hand gestures, or other limb actions; kicking actions include vertical kicks, horizontal kicks, etc.; this embodiment and subsequent embodiments use tailgate control as the vehicle control and kicking action as the target action as an example for explanation. Other types of vehicle control and actions can be implemented by analogy and will not be described in detail.

[0031] The target action is the action performed by the user as determined by the method described in this embodiment.

[0032] It is understandable that different kicking actions have different characteristics. For example, the characteristics of a vertical kick are that the foot kicks out towards the rear of the car first and then retracts; the characteristics of a horizontal kick are that the foot kicks out to the left and forward first, then moves laterally, and then retracts. Therefore, when setting kicking actions, the motion characteristics of the kicking action are set based on the specific type of kicking action. In practical applications, the user's motion characteristics are detected, and the detected motion characteristics are matched with the motion characteristics of the kicking action to determine the target action.

[0033] It is understood that in this embodiment, the directional velocity feature reflects the motion of objects within the detection area of ​​the ultra-wideband radar, while the motion feature reflects the type of motion. The target action is then determined based on the motion feature matching. In this embodiment, the action is determined based on the characteristics of the kicking action. Therefore, it can avoid false triggering of the kicking action detection caused by objects accidentally approaching the vehicle in the environment, and can improve the accuracy of kicking action detection.

[0034] This embodiment uses an ultra-wideband radar to determine the directional velocity characteristics of target objects within the detection area, thereby identifying the motion characteristics of the target objects within the detection area and reflecting their motion. Based on this motion, the corresponding target action is matched, enabling detection based on the actual motion characteristics of the kicking action, thus improving detection accuracy.

[0035] Further details will follow. Figure 3 In the second embodiment of the motion detection method of the present invention based on the first embodiment, step S20 includes the following steps: Step S21: Determine the signal phase change rate of the channel impulse response data and determine the object direction corresponding to the channel impulse response data; Step S22: Match the signal frequency shift corresponding to the phase change rate of the matched signal; Step S23: Obtain the signal wavelength corresponding to the channel impulse response data, and calculate the object velocity based on the signal wavelength and signal frequency shift; Step S24: Associate the object velocity with the object direction to obtain the directional velocity feature.

[0036] The signal phase change rate is the rate of change of the phase of the signal received by the ultra-wideband radar, as reflected in the channel impulse response data. The signal phase change rate is obtained by dividing the phase difference of the received signals at two different times by the time interval between them. Specifically, the signal phase change rate can be determined based on the received signal corresponding to the previously transmitted pulse and the pulse transmitted in the current time.

[0037] The object direction refers to the relative motion direction of the object within the detection area relative to the ultra-wideband radar.

[0038] Signal frequency shift is a frequency change phenomenon caused by the relative motion between the wave source and the receiver; there is a direct relationship between signal frequency shift and the rate of change of signal phase:

[0039] Among them, f d For signal frequency shift; The rate of change of the signal phase; t represents the pulse repetition period of the ultra-wideband radar.

[0040] The signal wavelength is the wavelength of the output signal of the ultra-wideband radar; the specific value of the signal wavelength can be set based on actual needs.

[0041] The object velocity is the moving speed of the target object relative to the ultra-wideband radar; based on the Doppler frequency shift formula, there is a corresponding relationship between the object velocity, signal wavelength, and signal frequency shift:

[0042] Where v is the velocity of the object; λ is the wavelength of the signal.

[0043] The object velocity indicates the speed at which the target object moves relative to the ultra-wideband radar, and the object direction indicates the direction of movement of the target object relative to the ultra-wideband radar. Therefore, by combining the object velocity and the object direction, we can reflect the motion of the target object relative to the ultra-wideband radar, thus obtaining the directional velocity characteristics that reflect the directional movement relative to the ultra-wideband radar.

[0044] Further, step S21 includes the following steps: Step S211: Perform wavelet analysis on the channel impulse response data to obtain the positive signal energy and negative signal energy; Step S212: If the positive signal energy is greater than the first energy threshold, the direction of the object is determined to be away from the ultra-wideband radar, where the first energy threshold is a positive number. If the positive signal energy is less than or equal to the first energy threshold, then the direction of the object is determined to be not far from the ultra-wideband radar, where the first energy threshold is a positive number; Step S213: If the negative signal energy is less than the second energy threshold, the direction of the object is determined to be close to the ultra-wideband radar, where the second energy threshold is a negative number.

[0045] If the negative signal energy is greater than or equal to the second energy threshold, then the direction of the object is determined to be not close to the ultra-wideband radar.

[0046] If the positive signal energy is less than or equal to the first energy threshold and the negative signal energy is greater than or equal to the second energy threshold, then it is considered that no kicking action was detected.

[0047] Wavelet analysis is a multi-resolution signal processing technique that can simultaneously capture the time and frequency domain features of a signal. Specifically, it uses wavelet basis functions to perform convolution operations on channel impulse response data to decompose signal components of different scales. The signal energy can be obtained by squaring or taking the modulus of the signal components.

[0048] Positive signal energy corresponds to the signal energy generated by motion moving away from the ultra-wideband radar.

[0049] Negative signal energy corresponds to the signal energy generated by motion approaching the ultra-wideband radar.

[0050] In practice, positive wavelet analysis can be performed on the channel impulse response data to obtain positive signal energy, and negative wavelet analysis can be performed on the channel impulse response data to obtain negative signal energy.

[0051] The energy threshold is the threshold for triggering motion detection; the first energy threshold is the energy threshold set for motion that is far away from the ultra-wideband radar, and the second energy threshold is the energy threshold set for motion that is close to the ultra-wideband radar; the specific value of the energy threshold can be set based on actual needs.

[0052] It is understandable that in practical applications, due to the complexity of environmental factors, objects that can be detected by accidental displacement may interfere with the detection of kicking actions. Therefore, in order to avoid the influence of accidental factors, an energy threshold is set in this embodiment. When the signal energy meets the energy threshold requirement, it is considered that a kicking action may have occurred, and the object direction is determined to proceed with subsequent steps. When the signal energy does not meet the energy threshold requirement, it is considered that no kicking action has occurred.

[0053] In this embodiment and subsequent embodiments, a positive direction indicates moving away from the ultra-wideband radar, and a negative direction indicates moving closer to the ultra-wideband radar; this will not be elaborated further.

[0054] Further, see Figure 4 Step S21 includes the following steps: Step S214: Perform wavelet analysis on the channel impulse response data within the current noise detection period to obtain the signal energy; Step S215: Convert the signal energy into signal decibels and calculate the average signal decibels within the current noise detection period; Step S216: Obtain the historical noise decibel level of the previous noise detection cycle, and combine the average signal decibel level with the historical noise decibel level to obtain the noise decibel level of the current cycle; Step S217: Subtract the current period noise decibel from the average signal decibel to obtain the target signal; Step S218: Determine the signal phase change rate of the target signal.

[0055] Signal decibels indicate the signal strength corresponding to the signal energy; specifically:

[0056] Where dB is the signal decibel; E signal This refers to signal energy.

[0057] The current noise detection period is a noise statistics window; the length of the current noise detection period can be set according to actual needs, such as setting the current noise detection period to 3 times the pulse repetition period of the ultra-wideband radar; it can be understood that the current noise detection period is a sliding window; taking 3 times the pulse repetition period as an example, the current noise detection period averages the signal decibels corresponding to the three pulse repetition periods n, n-1, and n-2 to obtain the average signal decibels, where n is the current pulse period.

[0058] The previous noise detection period is the noise detection period corresponding to the n-1 pulse repetition period, which is specifically determined based on the signal decibels corresponding to the three pulse repetition periods n-1, n-2, and n-3.

[0059] The historical noise decibel is the noise decibel determined in the previous noise detection cycle; it can be understood that the historical noise decibel of the previous noise detection cycle is obtained by the average signal decibel determined in the previous noise detection cycle and the historical noise decibel of the noise detection cycle before that.

[0060] In practical applications, sudden environmental events may cause abrupt changes in signal noise. Therefore, in order to avoid significant changes in signal processing due to sudden events, this embodiment combines the historical noise decibels of the previous noise detection cycle with the average signal decibels of the current noise detection cycle to comprehensively determine the current period noise decibels of the current noise detection cycle; thereby enabling the noise decibels to be updated smoothly and eliminating the impact of sudden events.

[0061] Specifically, the current periodic noise level can be calculated by weighted summation using the average signal level in decibels and historical noise levels in decibels:

[0062] Where noise is the current periodic noise in decibels; old_noise is the historical noise in decibels; ave_dB is the average signal in decibels; and A is the weight of the historical noise in decibels. The specific value can be set according to actual needs.

[0063] After obtaining the current period noise level in decibels, subtracting the current period noise level from the average signal level in decibels yields the denoised signal, i.e., the target signal.

[0064] Where snr is the target signal.

[0065] It should be noted that signal energy includes positive signal energy and negative signal energy. The positive signal energy can be denoised to obtain the positive target signal, and the negative signal energy can be denoised to obtain the negative target signal. The corresponding signal phase change rate can then be obtained from the positive and negative target signals.

[0066] The signal phase change rate is determined based on the denoised target signal, which enables the elimination of environmental background noise interference and improves detection accuracy.

[0067] Further, see Figure 5 Step S218 includes the following steps: Step S2181: Retain the maximum frequency signal corresponding to each moment in the target signal, and combine the maximum frequency signals corresponding to each moment to obtain the target frequency signal; Step S2182: Determine the signal phase change rate corresponding to the target frequency signal.

[0068] The maximum frequency signal is the signal with the largest absolute frequency at a given moment.

[0069] It is understandable that the signal received by the ultra-wideband radar at the same moment contains environmental interference, such as the slight shaking of ground debris, which has a very low frequency. However, when a kicking action occurs, the signal received by the ultra-wideband radar due to the kicking action has a higher frequency. Therefore, in order to further avoid the influence of environmental factors, in this embodiment, only the signal with the highest frequency is selected to determine the signal phase change rate, so as to have a strong sensitivity to the real kicking action and reduce the impact of environmental interference.

[0070] Furthermore, in the third embodiment of the motion detection method of the present invention based on the first embodiment, the directional velocity feature includes the object direction and the object velocity; step S30 includes the following steps: Step S31: Determine multiple directional velocity features that are continuous, have the same object direction, and have an object velocity greater than a preset velocity threshold; Step S32: Determine whether the duration of the velocity features in multiple directions is greater than a preset time threshold. Step S33: If the duration of multiple directional velocity features is greater than a preset time threshold, then the detected motion feature is determined to be a unidirectional movement feature, wherein the direction of the unidirectional movement feature is the object direction corresponding to the multiple directional velocity features.

[0071] The kicking action is a continuous action, and the motion characteristics reflect the specific type of kicking action. In this embodiment, the motion characteristics are determined by continuously defined directional velocity characteristics.

[0072] In this embodiment, continuous directional velocity characteristics refer to directional velocity characteristics determined by continuous pulse repetition periods in an ultra-wideband radar, such as directional velocity characteristics determined by n-1 and n being continuous directional velocity characteristics.

[0073] The preset speed threshold indicates the minimum speed required for a kicking motion; the specific value can be set based on actual needs; the preset speed threshold can be set separately for positive and negative object speeds, with positive speed thresholds being positive numbers and negative speed thresholds being negative numbers.

[0074] It is understandable that when a kicking action occurs, its corresponding motion characteristics usually exhibit similar motions for a certain duration. For example, a kick will continuously approach the ultra-wideband radar for a certain period of time. In terms of directional velocity characteristics, if the kick begins in cycle T1, then in the previous cycle, T0, the directional velocity characteristics show that the object direction is negative or the object velocity is greater than the negative velocity threshold. In cycle T1, the directional velocity characteristics show that the object direction is negative and the object velocity is less than the negative velocity threshold. During the duration of the kick, the directional velocity characteristics consistently show that the object direction is negative and the object velocity is less than the negative velocity threshold. When the kick ends, such as in cycle Tx, the directional velocity characteristics show that the object direction is positive or the object velocity is greater than the negative velocity threshold. At this point, it can be determined that the kicking action occurred in cycles T1 to Tx, reflecting multiple directional velocity characteristics with continuous, negative object direction and object velocity less than the negative velocity threshold, thus identifying the kicking action.

[0075] For example, regarding leg retraction, the object will continuously move away from the ultra-wideband radar for a certain period of time. This is reflected in the directional velocity characteristics. If leg retraction begins in cycle T1, then in the previous cycle (T0), the directional velocity characteristics show the object's direction as negative or its velocity as less than the positive velocity threshold. In cycle T1, the directional velocity characteristics show the object's direction as positive and its velocity as greater than the positive velocity threshold. Throughout the leg retraction cycle, the directional velocity characteristics consistently show the object's direction as positive and its velocity as greater than the positive velocity threshold. When leg retraction ends, such as in cycle Tx, the directional velocity characteristics show the object's direction as positive or its velocity as greater than the positive velocity threshold. At this point, it can be determined that the leg retraction action occurred between cycles T1 and Tx, reflecting multiple directional velocity characteristics with continuous, negative object directions and object velocities greater than preset velocity thresholds, thus identifying the leg retraction action.

[0076] Therefore, by analyzing multiple directional velocity features that are continuous, have the same object orientation, and have an object speed greater than a preset speed threshold, it is possible to identify features of single-direction movement, such as positive or negative movement.

[0077] In practical applications, since the kicking and retracting movements require a certain duration, this embodiment sets a preset time threshold to determine the minimum duration determined by the movement characteristics; the specific value of the preset time threshold can be set based on actual needs.

[0078] Therefore, if a movement meets the unidirectional motion characteristic and the duration requirement for motion execution is met, it can be determined as a unidirectional movement characteristic.

[0079] It should be noted that some action features involve multiple directions. For example, for a side kick from left to right, the kicker will first approach the ultra-wideband radar at a slightly slower speed than the kicking leg. After the foot moves directly towards the ultra-wideband radar, it will then move away from the ultra-wideband radar at a slightly slower speed than the retraction leg. In this case, a speed range and a negative-to-positive directional arrangement can be set for the side kick as conditions for determining the action features, thereby determining the action features of the composite direction.

[0080] Furthermore, in the fourth embodiment of the motion detection method of the present invention based on the first embodiment of the present invention, step S40 includes the following steps: Step S41: Obtain multiple continuously defined motion features; Step S42: Obtain the motion feature arrangement according to the detection order of the motion features; Step S43: In the preset kicking action, match the kicking action that is consistent with the preset feature arrangement and the motion feature arrangement; Step S44: Match the kicking motion as the target motion.

[0081] In this embodiment, the continuity of motion features refers to the continuity of the sequence of motion features. Periods of undetermined motion features are allowed between consecutive motion features. At the same time, a preset number of periods can be set. When the target action is not clearly determined for a consecutive preset number of periods, the previously determined motion features are discarded.

[0082] The detection order of motion features is the chronological order in which the motion features are determined. For example, motion features determined by n-1 pulse repetition cycles precede motion features determined by n pulse repetition cycles.

[0083] The motion feature arrangement is a set obtained by arranging motion features in the order of detection.

[0084] For a specific kicking action, it can be broken down into the sequential execution of multiple action features. Therefore, a preset feature arrangement is set for each kicking action in advance, such as: See Figure 6 For example, if the kicking action is a vertical kick, then its corresponding preset feature arrangement is kicking (close to the ultra-wideband sensor) and retracting the leg (away from the ultra-wideband sensor).

[0085] See Figure 7 For example, if the kicking action is a side kick, the corresponding preset feature arrangement is: kicking (approaching the ultrawideband sensor and the speed decreases from large to small), side kicking (approaching and then moving away from the ultrawideband sensor), and retracting the leg (moving away from the ultrawideband sensor).

[0086] When the actual detected motion feature arrangement matches the preset feature arrangement of a certain kicking action, it is determined that the kicking action has been detected, that is, the target action is determined.

[0087] It should be noted that a match can be determined as long as the motion feature arrangement contains a preset kicking action. For example, if the motion feature arrangement is leg retraction, kicking, and leg retraction, then it contains the preset feature arrangement corresponding to the vertical kick of kicking and retraction. Therefore, a vertical kick is detected.

[0088] In this embodiment, the target action can be accurately determined by matching the sequential arrangement of motion features.

[0089] Further, the following steps are included after step S42: Step S45: Obtain the motion cycle features arranged by motion features; Step S46: Determine whether the action cycle features meet the action recognition conditions; Step S47: If the motion cycle features meet the motion recognition conditions, then match the kicking motion based on the motion features.

[0090] The motion cycle feature is the related signal feature of the cycle designed by arranging motion features; specifically, it can include velocity features, time features, acceleration features, etc.

[0091] The action recognition condition is that when a kicking action occurs, the motion feature arrangement must have the motion periodic features.

[0092] It is understandable that in practical applications, due to environmental interference, there may be scenarios that conform to the characteristics of a kicking action, which may lead to accidental touches. Therefore, in this embodiment, in addition to the features, action recognition conditions are set for the action cycle characteristics of the signal to further set the conditions for the signal characteristics of the kicking scene, thereby further reducing the probability of accidental touches.

[0093] Further, step S46 includes the following steps: Step S461: Obtain the maximum velocity, maximum acceleration, and cycle duration from the motion cycle features; Step S462: Determine whether the maximum speed is within the preset speed range, whether the maximum acceleration is greater than the preset acceleration threshold, and whether the period duration is less than the preset duration threshold. Step S463: If the maximum speed is within the preset speed range, the maximum acceleration is greater than the preset acceleration threshold, and the period duration is less than the preset duration threshold, then the action recognition condition is met.

[0094] The maximum velocity is determined among all moments in the sequence of motion characteristics. Figure 6 , 7 Chinese f cf is the maximum negative velocity in the maximum velocity range. s This is the maximum positive velocity within the maximum speed range.

[0095] The preset speed range is the required speed range for a kicking motion. The specific value can be set based on actual needs. It is understood that in practical applications, kicking motions are usually within a certain speed range. Therefore, in order to distinguish them from environmental interference, the possible speeds of kicking motions are set to obtain the preset speed range, and the maximum speed is evaluated based on the preset speed range to clarify the possibility of kicking motions.

[0096] The maximum acceleration is the maximum acceleration determined across all moments in the sequence of motion characteristics; Figure 6 , 7 In the equation, a1 represents the maximum negative acceleration within the maximum acceleration, and a2 represents the maximum positive acceleration within the maximum acceleration.

[0097] The preset acceleration threshold is the acceleration requirement set for kicking movements; the specific value can be set based on actual needs. Kicking movements typically exhibit certain acceleration characteristics, such as a significant acceleration at the initial stage of the kick. Therefore, to match the characteristics of kicking movements, a preset acceleration threshold is set to determine the likelihood of a kicking action based on acceleration. It should be noted that different motion characteristics have different acceleration requirements. Therefore, a corresponding preset acceleration threshold can be set for each motion characteristic based on its type, and the motion characteristic can be compared with the corresponding preset acceleration threshold. The preset acceleration threshold requirement is met when the maximum acceleration of all motion characteristics is greater than the corresponding preset acceleration threshold.

[0098] The period duration is the time difference between the earliest and latest signals from the signal sources of the motion feature arrangement; Figure 6 , 7 C s S is the earliest signal acquisition time. e This is the latest time the signal was acquired.

[0099] The preset duration threshold is the required completion time for the kicking action. To avoid environmental interference, this embodiment sets a more difficult condition to meet, that is, the kicking action must be completed within the preset duration threshold, thereby reducing the execution time of the kicking action. The shorter the time, the more difficult it is for environmental interference to mistakenly trigger the kicking action, thus reducing the probability of mistaken triggering.

[0100] In this embodiment, by setting corresponding conditions for the maximum speed, maximum acceleration, and cycle duration in the action cycle characteristics, it is possible to further combine the characteristics of the kicking action to set signal feature requirements, thereby further reducing the misidentification of environmental interference noise.

[0101] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0102] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0103] The present invention also provides a motion detection system, including a processor and a memory connected to the processor, wherein the memory stores program code for a data acquisition module, program code for a direction and velocity feature module, program code for a motion feature module, and program code for a matching module. The processor is configured to execute the data acquisition module program code to continuously acquire channel impulse response data collected by the ultra-wideband radar; The processor is also configured to execute directional velocity feature module code to determine the directional velocity features corresponding to the channel impulse response data; The processor is also configured to execute motion feature module code to determine the motion features of the target object based on the directional velocity features; The processor is also configured to execute matching module code to match the target action corresponding to the motion feature.

[0104] Reference Figure 8 In terms of hardware structure, the motion detection device may include components such as a communication module 10, a memory 20, and a processor 30. In the motion detection device, the processor 30 is connected to both the memory 20 and the communication module 10. The memory 20 stores a computer program, which is executed by the processor 30. When the computer program is executed, it implements the steps of the above-described method embodiments.

[0105] The communication module 10 can connect to external communication devices via a network. The communication module 10 can receive requests from external communication devices, and can also send requests, instructions and information to external communication devices. External communication devices can be other motion detection devices, servers or Internet of Things devices, such as televisions, etc.

[0106] The memory 20 can be used to store software programs and various data. The memory 20 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as continuously acquiring channel impulse response data collected by ultra-wideband radar), etc.; the data storage area may include a database, and may store data or information created based on system usage. Furthermore, the memory 20 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0107] The processor 30 is the control center of the motion detection device. It connects various parts of the device via interfaces and lines, and performs various functions and processes data by running or executing software programs and / or modules stored in the memory 20, and by calling data stored in the memory 20, thereby providing overall monitoring of the motion detection device. The processor 30 may include one or more processing units; optionally, it may integrate an application processor and a modem processor. The application processor primarily handles the operating system, user interface, and applications, while the modem processor primarily handles wireless communication. It is understood that the modem processor may not be integrated into the processor 30.

[0108] although Figure 8 Not shown, but the above-described motion detection device may further include a circuit control module, which is connected to a power supply to ensure the normal operation of other components. Those skilled in the art will understand that... Figure 8 The motion detection device structure shown does not constitute a limitation on the motion detection device. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0109] This invention also proposes a computer-readable storage medium on which a computer program is stored. The computer-readable storage medium may be... Figure 8The memory 20 in the motion detection device may be at least one of ROM (Read-Only Memory) / RAM (Random Access Memory), magnetic disk, optical disk, etc. The computer-readable storage medium includes several instructions to cause a terminal device with a processor (which may be a television, automobile, mobile phone, computer, server, terminal, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0110] In this invention, the terms "first," "second," "third," "fourth," and "fifth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0111] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0112] Although embodiments of the present invention have been shown and described above, the scope of protection of the present invention is not limited thereto. It is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, and substitutions to the above embodiments within the scope of the present invention, and such changes, modifications, and substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A motion detection method, characterized in that, The motion detection method includes: Continuously acquire channel impulse response data collected by ultra-wideband radar; Determine the directional velocity characteristics corresponding to the channel impulse response data; The motion characteristics of the target object are determined based on the directional velocity characteristics; Match the target action corresponding to the motion feature.

2. The motion detection method as described in claim 1, characterized in that, The determination of the directional velocity characteristics corresponding to the channel impulse response data includes: Determine the signal phase change rate of the channel impulse response data, and determine the object orientation corresponding to the channel impulse response data; Match the signal frequency shift corresponding to the rate of change of the signal phase; Obtain the signal wavelength corresponding to the channel impulse response data, and calculate the object velocity based on the signal wavelength and the signal frequency shift; The directional velocity feature is obtained by associating the object's velocity with the object's direction.

3. The motion detection method as described in claim 2, characterized in that, The determination of the object direction corresponding to the channel impulse response data includes: Wavelet analysis is performed on the channel impulse response data to obtain the positive and negative signal energies; If the positive signal energy is greater than the first energy threshold, then the direction of the object is determined to be away from the ultra-wideband radar, wherein the first energy threshold is a positive number; If the negative signal energy is less than the second energy threshold, then the direction of the object is determined to be close to the ultra-wideband radar, wherein the second energy threshold is a negative number.

4. The motion detection method as described in claim 2, characterized in that, The method for determining the signal phase change rate of the channel impulse response data includes: The signal energy is obtained by wavelet analysis of the channel impulse response data within the current noise detection period; The signal energy is converted into signal decibels, and the average signal decibels within the current noise detection period are calculated; Obtain the historical noise decibel level of the previous noise detection cycle, and combine the average signal decibel level with the historical noise decibel level to obtain the noise decibel level of the current cycle; The target signal is obtained by subtracting the current period noise level from the average signal level in decibels. Determine the rate of change of the target signal's phase.

5. The motion detection method as described in claim 4, characterized in that, Determining the phase change rate of the target signal includes: The maximum frequency signal corresponding to each moment in the target signal is retained, and the target frequency signal is obtained by combining the maximum frequency signals corresponding to each moment. Determine the rate of change of the signal phase corresponding to the target frequency signal.

6. The motion detection method as described in claim 1, characterized in that, The directional velocity feature includes the object's direction and object's velocity; determining the motion features of the target object based on the directional velocity feature includes: Identify multiple directional velocity features that are continuous, have the same direction, and have a velocity greater than a preset velocity threshold. Determine whether the duration of the multiple directional velocity features is greater than a preset time threshold. If the duration of multiple directional velocity features is greater than the preset time threshold, then the detected motion feature is determined to be a unidirectional movement feature, wherein the direction of the unidirectional movement feature is the object direction corresponding to the multiple directional velocity features.

7. The motion detection method as described in claim 1, characterized in that, The target action matched with the motion feature includes: Obtain a plurality of continuously defined motion features; The motion features are arranged according to the detection order of the motion features; In the preset kicking motion, a matching kicking motion is matched with a preset feature arrangement that is consistent with the motion feature arrangement; The matching kicking motion is taken as the target motion.

8. The motion detection method as described in claim 7, characterized in that, The step of arranging the motion features according to the detection order of the motion features includes: Obtain the motion cycle features of the motion feature arrangement; Determine whether the action cycle characteristics meet the action recognition conditions; If the motion cycle feature satisfies the motion recognition condition, then the matching kicking motion is arranged and matched based on the motion feature.

9. The motion detection method as described in claim 8, characterized in that, Determining whether the action cycle feature satisfies the action recognition condition includes: Obtain the maximum speed, maximum acceleration, and cycle duration from the action cycle characteristics; Determine whether the maximum speed is within a preset speed range, whether the maximum acceleration is greater than a preset acceleration threshold, and whether the period duration is less than a preset duration threshold; If the maximum speed is within a preset speed range, the maximum acceleration is greater than a preset acceleration threshold, and the period duration is less than a preset duration threshold, then the action recognition condition is met.

10. A motion detection system, characterized in that, It includes a processor and a memory connected to the processor. The memory stores the program code of the data acquisition module, the program code of the direction and velocity feature module, the program code of the motion feature module, and the program code of the matching module. The processor is configured to execute the data acquisition module program code to continuously acquire channel impulse response data collected by the ultra-wideband radar; The processor is also configured to execute directional velocity feature module code to determine the directional velocity features corresponding to the channel impulse response data; The processor is also configured to execute motion feature module code to determine the motion features of the target object based on the directional velocity features; The processor is also configured to execute matching module code to match the target action corresponding to the motion feature.

11. A motion detection device, characterized in that, The motion detection device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the motion detection method as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the motion detection method as described in any one of claims 1 to 9.

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