Configuration method and device of safety monitoring system, electronic equipment and storage medium

Abstract

The invention provides a configuration method for a safety monitoring system, and the method comprises the steps: receiving point cloud data of a point cloud data collection device for a target region, and configuring the target region into a three-dimensional space for display in an operation interface; configuration parameters of a user for the event are received, an event monitoring area is configured in the operation interface according to the configuration parameters, and the configuration parameters comprise an area type, an area frame parameter and an event monitoring algorithm; and performing event monitoring on the event monitoring area based on the configured point cloud data of the event monitoring area and the target area. According to the invention, by introducing the combination of the upper computer and the point cloud data acquisition device and corresponding software algorithm support, three-dimensional space display and event monitoring of the target area can be realized, so that the accuracy and flexibility of safety monitoring are improved.

Description

Technical Field

[0001] The present invention relates to the field of visual technology, and in particular to a configuration method, device, electronic equipment and storage medium for a security monitoring system. Background Art

[0002] Stereo safety sensors, also known as Time-of-Flight (ToF) cameras or 3D TOF cameras, are mainly used for stereo protection in the industrial field. Their working principle is to calculate the distance information by measuring the time it takes for light to be emitted from the stereo safety sensor to the object in the detection area and then reflected back to the camera, thereby obtaining the three-dimensional spatial data of the scene. When a target object invades the detected area, it will output a safety control signal to the host computer or relay, thereby controlling the shutdown of the working equipment.

[0003] At present, the functions of traditional security monitoring systems are fixed. For example, a system only monitors one type of event. When monitoring different events in different areas, additional system hardware facilities are required. Therefore, the configuration of existing security monitoring systems is fixed, with poor flexibility, and cannot adapt to monitoring scenarios with diverse requirements. Summary of the invention

[0004] The embodiment of the present invention provides a configuration method for a security monitoring system, which can improve the accuracy of detection area monitoring and improve the work efficiency of the system. By receiving the point cloud data of the target area from the point cloud data acquisition device, and configuring the target area as a three-dimensional space to be displayed in the operation interface, receiving the configuration parameters of the user for the event, and configuring the event monitoring area in the operation interface according to the configuration parameters, and using the configured event monitoring area and the point cloud data of the target area to perform event monitoring on the event monitoring area, by introducing a combination of a host computer and a point cloud data acquisition device, and corresponding software algorithm support, the three-dimensional space display and event monitoring of the target area can be realized, thereby improving the accuracy and flexibility of security monitoring.

[0005] In a first aspect, an embodiment of the present invention provides a configuration method of a safety monitoring system, wherein the safety monitoring system includes a host computer and at least one point cloud data acquisition device, wherein the host computer includes an operation interface for interaction, and the point cloud data acquisition device is used to collect point cloud data of a target area, and the method includes the following steps:

[0006] Receiving point cloud data of the target area from the point cloud data acquisition device, and configuring the target area to be displayed in the operation interface as a three-dimensional space;

[0007] Receiving configuration parameters for an event from a user, and configuring an event monitoring area in the operation interface according to the configuration parameters, wherein the configuration parameters include an area type, an area frame parameter, and an event monitoring algorithm;

[0008] Based on the configured event monitoring area and the point cloud data of the target area, event monitoring is performed on the event monitoring area.

[0009] Optionally, configuring the event monitoring area in the operation interface according to the configuration parameters includes:

[0010] According to the area type, matching the event monitoring algorithm corresponding to the area type in the event monitoring algorithm library, wherein different area types correspond to different event monitoring algorithms in the event monitoring algorithm library;

[0011] Drawing an area frame in the three-dimensional space according to the area frame parameters;

[0012] The event monitoring algorithm is associated with the area frame, and an event monitoring area is configured in the operation interface.

[0013] Optionally, the area frame parameters include a frame length, a frame width, and a frame height, and drawing the area frame in the three-dimensional space according to the area frame parameters includes:

[0014] In the three-dimensional space, determining the three-dimensional coordinates of the positioning point of the target;

[0015] According to the frame length, the frame width, the frame height and the three-dimensional coordinate values ​​of the positioning points, an area frame is drawn in the three-dimensional space, and each of the targets corresponds to one area frame.

[0016] Optionally, performing event monitoring on the event monitoring area based on the configured point cloud data of the event monitoring area and the target area includes:

[0017] receiving a selection instruction from a user, and selecting at least one target event monitoring area from among the configured event monitoring areas;

[0018] Based on the point cloud data of the target area and in combination with the event monitoring algorithm corresponding to the target event monitoring area, event monitoring is performed on the target event monitoring area.

[0019] Optionally, performing event monitoring on the event monitoring area based on the configured point cloud data of the event monitoring area and the target area includes:

[0020] receiving a switching instruction from a user, and determining a target event monitoring area in the event monitoring area;

[0021] Switching the current event monitoring area to the target event monitoring area;

[0022] Based on the point cloud data of the target area and in combination with the event monitoring algorithm corresponding to the target event monitoring area, event monitoring is performed on the target event monitoring area.

[0023] Optionally, the area type includes at least one of a shielding area, a protection area, an alarm area, a contour analysis area, a focus area, and an AI analysis area, and the event monitoring of the event monitoring area based on the configured point cloud data of the event monitoring area and the target area includes:

[0024] If the configured event monitoring area is a protection area or an alarm area, determining whether there is an intrusion event in the protection area or the alarm area based on each two-dimensional projection plane of the protection area or the alarm area, and if there is an intrusion event in the protection area or the alarm area, outputting a first safety control signal;

[0025] If the configured event monitoring area is a focus area, determining whether there is an intrusion event in the focus area based on the depth discrete rate of each point cloud in the focus area, and outputting a second safety control signal if there is an intrusion event in the focus area;

[0026] If the configured event monitoring area is a contour analysis area, determining whether there is a contour change event in the contour analysis area based on the distance change between the reference frame point cloud data of the contour analysis area and each point cloud in the current frame point cloud data, and outputting a third safety control signal if there is a contour change event in the contour analysis area;

[0027] If the configured event monitoring area is an AI analysis area, it is determined whether there is a target person in the AI ​​analysis area based on the intensity image data and the three-dimensional point cloud data. If there is a target person in the AI ​​analysis area, a fourth safety control signal is output.

[0028] In a second aspect, an embodiment of the present invention further provides a configuration device for a safety monitoring system, the safety monitoring system comprising a host computer and at least one point cloud data acquisition device, the host computer comprising an operation interface for interaction, the point cloud data acquisition device being used to collect point cloud data of a target area, the configuration device for the safety monitoring system comprising:

[0029] A first configuration module is used to receive point cloud data of the target area from the point cloud data acquisition device, and configure the target area to be displayed in the operation interface as a three-dimensional space;

[0030] A second configuration module is used to receive configuration parameters of an event from a user and configure an event monitoring area in the operation interface according to the configuration parameters, wherein the configuration parameters include an area type, an area frame parameter, and an event monitoring algorithm;

[0031] The event monitoring module performs event monitoring on the event monitoring area based on the configured point cloud data of the event monitoring area and the target area.

[0032] In a third aspect, an embodiment of the present invention provides a security monitoring system, which includes a host computer and at least one point cloud data acquisition device, the host computer includes an operation interface for interaction, the point cloud data acquisition device is used to collect point cloud data of a target area, and the host computer is used to execute the steps in the configuration method of the security monitoring system provided in an embodiment of the present invention.

[0033] In a fourth aspect, an embodiment of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps in the method for configuring the security monitoring system provided in the embodiment of the present invention when executing the computer program.

[0034] In a fifth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in the configuration method of the security monitoring system provided in the embodiment of the invention are implemented.

[0035] In an embodiment of the present invention, point cloud data of a target area is received from a point cloud data acquisition device, and the target area is configured as a three-dimensional space for display in an operation interface; configuration parameters of an event from a user are received, and an event monitoring area is configured in the operation interface according to the configuration parameters, and the configuration parameters include area type, area frame parameters, and event monitoring algorithm; based on the configured event monitoring area and point cloud data of the target area, event monitoring is performed on the event monitoring area. The present invention receives point cloud data of a target area from a point cloud data acquisition device, and configures the target area as a three-dimensional space for display in an operation interface, receives configuration parameters of an event from a user, and configures the event monitoring area in the operation interface according to the configuration parameters, and uses the configured event monitoring area and point cloud data of the target area to perform event monitoring on the event monitoring area. The present invention introduces a combination of a host computer and a point cloud data acquisition device, as well as corresponding software algorithm support, to achieve three-dimensional spatial display and event monitoring of the target area, thereby improving the accuracy and flexibility of safety monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 is a flow chart of a method for configuring a security monitoring system provided by an embodiment of the present invention;

[0038] Figure 2 is a structural schematic diagram of a configuration device for a safety monitoring system provided by an embodiment of the present invention;

[0039] Figure 3 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] An embodiment of the present invention provides a security monitoring system, which includes a host computer and at least one point cloud data acquisition device. The host computer includes an operation interface for interaction, the point cloud data acquisition device is used to collect point cloud data of a target area, and the host computer is used to execute the steps in the configuration method of the security monitoring system provided in the embodiment of the present invention.

[0042] Specifically, the above-mentioned safety monitoring system includes a point cloud acquisition module, a signal input module, a configuration module, a processing module and an output module.

[0043] The point cloud acquisition module is configured to acquire point cloud data of a target area, and the point cloud acquisition module is located in a point cloud data acquisition device.

[0044] The signal input module, configuration module, processing module and output module are located in the host computer.

[0045] The signal input module is configured to receive a zone group event switching signal, an external trigger signal, a reset signal, an EDM signal, a wake-up signal, a power input, etc.

[0046] The above configuration modules include an account management module, a network configuration module, a regional group configuration module, a regional configuration module, an input configuration module, an output configuration module, a working mode configuration module, a sleep / wake function configuration module, a collection end parameter configuration module and an event configuration module.

[0047] The account management module is used to add or delete accounts, or to manage account permissions.

[0048] The area group configuration module is used to configure the increase and decrease of area groups, the increase and decrease of areas within area groups, and area configuration. The area group can be understood as a set of areas composed of multiple areas of the same area type. Each area group corresponds to one area type. Of course, multiple areas of different area types can also be combined into one area group. Areas within an area group can be increased or decreased through the area configuration module.

[0049] The area configuration module is used for area drawing, area type (shielded area / alarm area / protected area / contour analysis area / ROI area / AI analysis area), output OSSD (OSSD, Output Switching Signal Device, output signal switching device) / IO type automatic adaptation, specific OSSD / IO output interface configuration, and output N / P type selection.

[0050] Input configuration module The input configuration module is used for OSSD reset mode configuration (manual / automatic), input delay configuration, EDM monitoring time configuration, etc. At the same time, it is used for regional group event input signal acquisition, input delay processing, input signal verification (parity check, etc.). It is also used for interrupt event input signals, specifically wake-up information (entering normal working state), external trigger signal (only effective when the camera mode is configured as external trigger mode, and only one 3D point cloud is collected once the external trigger is triggered).

[0051] The output configuration module is used for OSSD reset mode configuration.

[0052] The working mode configuration is used to configure the working mode, which can include live mode, soft trigger, and hardware trigger.

[0053] The sleep / wake function configuration module is used to configure the sleep / wake function.

[0054] The acquisition end parameter configuration module is used to configure the frame rate of the point cloud acquisition module, configure the camera exposure time, configure time synchronization, and configure the photo mode. Specifically, the configuration of the 3D point cloud acquisition module may include frame rate, camera exposure time, time synchronization, photo mode, filtering, etc. After configuring the point cloud acquisition module, you can collect point cloud data of the corresponding area.

[0055] The event configuration module is used for event storage configuration and event type configuration (event / sleep).

[0056] The processing modules may include an alarm area protection processing module (AI / traditional), a protection area protection processing module (AI / traditional), a contour recognition area protection processing module, and a ROI area (region of interest) protection processing module.

[0057] Among them, the alarm area is configured with resolution and resampling times. The resolution is configured to automatically calculate the farthest alarm distance corresponding to a smaller size threshold or object point threshold, and the resampling times are N. Alarm area intrusion detection (alarm area detection algorithm):

[0058] Step 1: Check whether there is a point cloud in the alarm area. If there is no point cloud, there is no intrusion IO output and no intrusion signal, otherwise proceed to the next step.

[0059] Step 2: Point cloud filtering processing. If there is no point cloud, there is no intrusion, and the IO output has no intrusion signal, otherwise proceed to the next step.

[0060] Step 3: Point cloud clustering processing, calculate the object size (or number of points). If the object size or the maximum number of object points is less than the threshold, there is no intrusion, and the I / O output has no intrusion signal, otherwise proceed to the next step.

[0061] Step 4: If the intrusion exceeds M1 times for N consecutive samplings, the IO outputs the intrusion signal.

[0062] The protection area is configured with resolution and resampling times. The resolution is configured to automatically calculate the maximum alarm distance - corresponding to a smaller size threshold, or object point threshold, and the resampling times are N. Protection area intrusion detection (protection area detection algorithm):

[0063] Step 1: Check whether there is a point cloud in the protection area. If there is no point cloud, there is no intrusion, and OSSD outputs a safety signal (no intrusion). Otherwise, proceed to the next step.

[0064] Step 2: Point cloud filtering processing. If there is no point cloud, there is no intrusion, and OSSD outputs a safety signal (no intrusion). Otherwise, proceed to the next step.

[0065] Step 3: Point cloud clustering processing, calculate the object size (or number of points). If the object size or the maximum number of object points is less than the threshold, there is no intrusion, and OSSD outputs a safety signal (no intrusion), otherwise proceed to the next step.

[0066] Step 4: If the intrusion exceeds M2 times for N consecutive samplings, OSSD will output a danger signal (intrusion).

[0067] Step 5: When the OSSD pre-output is a danger signal and a reset signal is received and there is no intrusion in the current frame, the OSSD resets and outputs a safety signal (no intrusion).

[0068] AI analysis area configuration increases or decreases AI analysis types: human body, head, hand, arm, leg, robot, AGV, helmet, safety clothing, etc.; automatically calculates the farthest analysis distance; identifies the access attribute configuration of the target type (access / no access); resampling times N. AI analysis area intrusion detection (AI zone detection algorithm):

[0069] Step 1. Perform AI analysis in the analysis area. If there is no point cloud in the analysis area, there is no intrusion and the OSSD outputs a safety signal (no prohibited target), otherwise proceed to the next step.

[0070] Step 2: Point cloud filtering processing. If there is no point cloud, there is no intrusion, and OSSD outputs a safety signal (no prohibited passage target), otherwise proceed to the next step.

[0071] Step 3, target identification and classification. If all targets are passable targets, the output is no intrusion, and the OSSD outputs a safety signal (no prohibited pass targets). If there are non-passable type targets, go to the next step.

[0072] Step 4: After N consecutive samplings, there are M3 intrusions, and OSSD outputs a danger signal (there is a prohibited target).

[0073] Step 5: When the OSSD pre-output is a danger signal and a reset signal is received, and there is no prohibited passage target in the current frame, the OSSD resets and outputs a safety signal (no prohibited passage target).

[0074] The contour analysis area configuration refers to the contour configuration, contour correlation threshold and resampling times. Contour analysis area abnormality detection (contour analysis area detection algorithm to prevent falling, etc.):

[0075] step1. Extract reference contour features.

[0076] Step 2: Extract the contour features of the current frame.

[0077] Step 3: Correlation analysis between the current frame contour and the reference contour (eg contour matching, etc.), combined with the correlation threshold, to determine whether the contour has undergone unacceptable changes.

[0078] Step 4. If the contour change is acceptable, the contour is normal and OSSD outputs safely. If the contour change is unacceptable, the contour is abnormal and OSSD outputs a danger signal.

[0079] Step 5: When the OSSD pre-output is a danger signal and a reset signal is received, and there is no prohibited passage target in the current frame, the OSSD resets and outputs a safety signal (no prohibited passage target).

[0080] ROI area configuration refers to ROI increase and decrease, ROI area size setting, ROI safety coordinate range configuration (including x, Y, Z coordinate range), and ROI area point repetition accuracy adjustment coefficient. ROI area anomaly detection (to prevent key point changes, corresponding to the area of ​​interest detection algorithm):

[0081] Step 1: For each ROI area, extract the coordinate data of all points in the ROI, and calculate the centroid coordinates and point repetition accuracy value.

[0082] Step 2: In the current frame, for each ROI point, calculate the centroid coordinates and repeatability of all points in the ROI.

[0083] Step 3. Determine whether the centroid coordinates of all ROIs are within the safe coordinate range. If the centroid coordinates of any ROI are within the safe coordinate range of the ROI area or the repetition accuracy of any ROI does not exceed the repetition accuracy threshold of the ROI area, it means that there are no unacceptable changes in all ROI areas, all ROIs are abnormal, and OSSD outputs a safety signal.

[0084] Step 4: If the centroid coordinates of any ROI exceed the safe coordinate range of the ROI point, or the repetition accuracy of any ROI exceeds the repetition accuracy threshold of the ROI area point, it means that there is an unacceptable change and the ROI has an abnormal OSSD output danger signal.

[0085] Step 5: The OSSD front output is a danger signal. The reset signal is currently received, and all ROIs in the current frame are normal. The OSSD resets and outputs a safety signal.

[0086] The shielding area is configured with dimensions (center coordinates, length, width, and height). The shielding area is generally used in conjunction with the alarm area / protection area / AI analysis area. There is no need to detect whether there is an intrusion in the shielding area within the alarm area. If the intrusion is within the alarm area and outside the shielding area, the IO outputs an intrusion alarm signal. There is no need to detect whether there is an intrusion in the shielding area within the protection area. If the intrusion is within the protection area and outside the shielding area, it means there is danger, and the OSSD outputs a danger signal. There is no need to detect whether there is a specific target intrusion in the shielding area within the AI ​​analysis area. If the specific target is within the AI ​​analysis area and outside the shielding area, it means there is danger, and the OSSD outputs a danger signal.

[0087] The above output modules are used for OSSD signals, IO signals, data output, etc. IO signal output can be configured as NPN / PNP output or adapted with input voltage. OSSD signal output can be configured to support NPN / PNP output, support OSSD and IO conversion configuration, OSSD heartbeat, and adapt with input voltage. Data output mode can be configured as point cloud output mode, depth map output mode, device information, etc.

[0088] In a possible embodiment, the host computer is a single channel (single processor), and can perform application solution processing based on the configuration, and configure the corresponding IO or OSSD output according to the configuration and event processing results.

[0089] In a possible embodiment, the host computer is dual-channel (dual processor), dual processor architecture, each channel self-check. Dual processor architecture, each channel is independent, cross-check. OSSD heartbeat design processing. Dual processors check each other. Dual processors and OSSD cross-check.

[0090] like Figure 1 As shown, Figure 1 1 is a flowchart of a method for configuring a security monitoring system provided by an embodiment of the present invention, the method for configuring a security monitoring system comprising the steps of:

[0091] 101. Receive point cloud data of a target area from a point cloud data acquisition device, and configure the target area as a three-dimensional space to be displayed in an operation interface.

[0092] In an embodiment of the present invention, the safety monitoring system includes a host computer and at least one point cloud data acquisition device. The point cloud data acquisition device can be a three-dimensional camera, a depth camera or a time-of-flight camera, such as a stereo safety sensor. The host computer includes an operating interface for interaction, and the point cloud data acquisition device is used to collect point cloud data of the target area.

[0093] The configuration method of the above security monitoring system is mainly used for the host computer of the security monitoring system. The above point cloud data can be understood as the three-dimensional coordinate data (x, y, z) of each pixel point in the depth map collected by the stereo security sensor.

[0094] The above-mentioned point cloud data can also be called 3D point cloud data. The collection of point cloud data in this embodiment can be based on the iTOF ranging principle. Through CW modulation driven by VCSEL, VCSEL modulates light with a frequency of f. Because it is necessary to analyze the phase difference between the reflected light and the emitted light to calculate the distance, in order to avoid multiple solutions, only the distance of the target within 1 / 2 wavelength can be measured, that is, the maximum ranging is 1 / 2 wavelength of the modulated light wave. The two frequencies of 15Mhz and 120Mhz adopted in this example, the theoretical maximum detection distance at 15Mhz frequency is 10m, and the theoretical maximum detection distance at 120Mhz frequency is 1.25m. The theoretical maximum detection distance of dual-frequency rotation is the least common multiple of the theoretical maximum detection distances corresponding to the two frequencies, that is, the greatest common multiple of 1.5m and 10m, that is, the theoretical maximum detection distance under the conditions of 15Mhz and 120Mhz rotation is 10m.

[0095] The distortion problem of the depth map is solved one by one through the camera intrinsic calibration. In the intrinsic calibration module, the common "pinhole + distortion" model in computer vision can be used to characterize the imaging system parameters such as lens distortion and principal point offset. The parameters include:

[0096] 1. Main point c x 、c y , represents the pixel coordinates of the intersection of the lens optical axis and the imaging target surface.

[0097] 2. Focal length f x 、f y , which represents the ratio of the lens focal length to the pixel size.

[0098] 3. Distortion parameters k1, k2, k 3； , p1, p2, where k1, k2, k3 are parameters representing the radial distortion of the lens, and p1 and p2 are parameters representing the tangential distortion of the lens. In the internal parameter calibration module, the calibration method is used to solve the model parameters. The camera is controlled to collect the intensity image of the calibration plate. Given the coordinates of the marking points in the calibration plate, the features of the marking points in the image are extracted to obtain the image coordinates of the marking points, the objective function is established, and the LM method is used for optimization and solution. Finally, the principal point c is obtained. x 、c y , focal length f x 、f y , and distortion parameters k1, k2, k3, p1, p2, and write the calibration results into the camera.

[0099] During the depth calibration (phase calibration) process, the measurement accuracy of TOF is affected by many factors. The depth calibration module mainly considers three items:

[0100] 1. When measuring an object with a distance of zero, when a zero-phase signal is transmitted, the delay difference between the phase of the signal received by RX (RF receiver) and the zero-phase signal is called zero drift.

[0101] 2. Characterize the zero drift that indicates the difference in the initial exposure time of different pixels, i.e., the fixed phase template noise.

[0102] 3. The deviation between the light waveform emitted by the TX (radio frequency transmitter) and the cosine signal causes harmonic errors that vary with distance.

[0103] The absolute errors introduced by the above items are usually in the order of centimeters. To ensure the accuracy of the distance measurement results, the above errors of each stereo safety sensor must be calibrated one by one before leaving the factory.

[0104] In order to calibrate the above errors, it is necessary to know the real distance of the object to be measured, collect TOF images at the same time, and calculate the actual measured distance. An error model is established between the two, and the model parameters are solved. In specific implementation, the stereo safety sensor is placed on the track table, and the 90% diffuse reflection plane is photographed at different distances to collect TOF data. The distance between the stereo safety sensor and the diffuse reflection plane given by the track table and the internal parameter calibration model are used to calculate the real distance of each pixel from the diffuse reflection plane. Call the depth calibration algorithm to process the collected TOF data, calculate the actual measurement distance, and optimize the model parameters.

[0105] The depth calculation algorithm completes the calculation from the raw image to the tap image, the tap image to the intensity image, the amplitude image, the phase image, the phase image to the distance image, the distance image to the depth image, and the depth image to the point cloud image. The depth calculation algorithm also has the following two functions:

[0106] 1. In the process of calculating the phase, the depth calculation algorithm needs to call the calibration results to compensate the calculated phase to eliminate the system error and obtain higher measurement accuracy.

[0107] 2. Because the stereo safety sensor works in dual-frequency mode, the depth calculation algorithm needs to fuse the dual-frequency data and output a higher quality measurement result after fusion.

[0108] The depth filtering algorithm is effective at different stages of the depth calculation algorithm, processing the intermediate quantities of the calculation, filtering out errors and low signal-to-noise ratio results, and ensuring the quality of the output results. The depth filtering algorithm consists of five modules:

[0109] 1. Temporal filtering module: averages multiple frames of the depth map to improve the signal-to-noise ratio. You can set the temporal filtering algorithm on and off, as well as the fusion weight of the current frame.

[0110] 2. Spatial filtering module: Perform spatial Gaussian filtering on the 1Q image to improve the signal-to-noise ratio. You can set the spatial filtering algorithm on and off, as well as the size of the Gaussian filtering window.

[0111] 3. Amplitude filter module: Set a certain threshold to filter out pixel depths with amplitudes below this threshold. You can set the amplitude filter algorithm on and off, as well as the amplitude filter threshold.

[0112] 4. Fusion error filter module: Calculate the dual-frequency fusion error. When the phase is greater than the set value, filter out the corresponding pixel depth. You can set the fusion error filter algorithm to open or close, as well as the size of the interval.

[0113] 5. Flying point filter module: convert the depth into point cloud, calculate the distance between the point and the surrounding points, and filter out the corresponding pixel depth when the minimum distance is greater than the set value. You can set the flying point filter to be on or off, as well as the size of the distance value.

[0114] The following is an example of point cloud generation:

[0115] Through CW modulation driven by VCSEL, VCSEL modulates two frequencies of light, 15MHz and 120MHz, respectively. The two frequencies of light are exposed under the illumination conditions to obtain energy integral images of four phases of 0°, 180°, 90°, and 270° at each frequency. Therefore, 8 energy integral images need to be collected together:

[0116] Rawdata120_0: 0° phase energy integration diagram under 120Mhz frequency modulated light.

[0117] Rawdata120_90: 90° phase energy integration diagram under 120Mhz frequency modulated light.

[0118] Rawdata120_180: 180° phase energy integration diagram under 120Mhz frequency modulated light.

[0119] Rawdata120_270: 270° phase energy integration diagram under 120Mhz frequency modulated light.

[0120] Rawdata15_0: 0° phase energy integration diagram under 15Mhz frequency modulated light.

[0121] Rawdata15_90: 90° phase energy integration diagram under 15Mhz frequency modulated light.

[0122] Rawdata15_180: 180° phase energy integration diagram under 15Mhz frequency modulated light.

[0123] Rawdata15_270: 270° phase energy integral diagram under 15Mhz frequency modulated light.

[0124] Dual frequency rotation:

[0125] 1. First, use 120MHz to take 4 pictures. Each picture has 2 phases (2 taps). The exposure time of each picture is the set exposure value (eg. the exposure is set to 1000us, 4 times of taking pictures is 4000us, and there is a waiting time between two pictures, the minimum is about 4ms).

[0126] 2. Then 15MHz, take 4 pictures, each picture has 2 phases (2 taps), and the exposure time of each picture is the set exposure value (eg. the exposure is set to 1000us, 4 photos are taken for 4 times, and there is a waiting time between two pictures, the minimum is about 4ms).

[0127] 3. At each modulation frequency, the tap phase sequence of the four figures is:

[0128] The tap sequence is (0°, 180°) → (90°, 270°) → (180°, 0°) → (270°, 90°).

[0129] The value of each pixel of Rawdata at a certain frequency and phase represents the integral of the target reflected energy at the direction corresponding to this pixel. For the same pixel, the integral energy Q0, Q 90 , Q 180 , Q 270 , the phase offset value of this point can be calculated

[0130]

[0131] Q0 represents the energy integral of the 0 phase of the pixel.

[0132] Q 90 Represents the energy integral of the 0 phase of the pixel.

[0133] Q 180 Represents the energy integral of the 0 phase of the pixel.

[0134] Q 270 Represents the energy integral of the 0 phase of the pixel.

[0135] According to the phase of the pixel The detection distance at this frequency can be calculated, and the corresponding distances d1 and d2 can be calculated for the two frequencies respectively.

[0136]

[0137] The final distance is obtained by dual-frequency solution.

[0138] (1) Calculate the dual-frequency integrated frequency.

[0139] f_max is the greatest common divisor of frequency f1 and frequency f2: when f1 = 15Mhz, f2 = 120Mhz, f_max = 15Mhz

[0140] (2) Calculate M_f1 and M_f2 as follows:

[0141] M_f1=f1 / f_max

[0142] M_f2=f2 / f_max

[0143] Calculate A_f1, A_f2 according to the following formula:

[0144]

[0145] Calculate ω according to the following formula:

[0146]

[0147] The final dual-frequency solution distance is:

[0148] d=d1·ω+d2·(1-ω)

[0149] Depth map generation:

[0150] ①According to the results of phase calibration, the relationship between the actual detected phase and the theoretical phase is obtained;

[0151] ② Based on the current actual detected phase, the current true phase can be calculated and converted into the calculated distance, which is the actual detection distance value.

[0152] Depth map converted into point cloud:

[0153] (1) Based on the calibration of the camera’s intrinsic parameters, the azimuth angle corresponding to each pixel can be obtained.

[0154] (2) Based on the depth d and azimuth, the three-dimensional coordinates x, y, and z can be calculated.

[0155] The above three-dimensional space can be understood as a three-dimensional coordinate system used to describe the position and shape of an object. The three-dimensional space is composed of three dimensions: length, width and height. The first three-dimensional space can be a camera monitoring area. The detection area can be set as a cube defined by vertices ABCDEFGH with the camera optical center O as the center, and six tetrahedrons (OABEH, OCDFG, OABCD, OEFGH, OADEF, OBCGH) in the cube as sub-areas.

[0156] The point cloud data of the target area is received from the point cloud data acquisition device, the point cloud data of the target area is uploaded to the host computer, and is visualized in the form of three-dimensional space through the operation interface of the host computer.

[0157] The above-mentioned operation interface refers to the graphical interface on the software or device for users to interact with the system.

[0158] The above three-dimensional space is used to describe the position and shape of an object, and the three-dimensional space is composed of three dimensions: length, width and height.

[0159] It should be noted that displaying the target area in the form of three-dimensional space in the operation interface can make the target area present a three-dimensional effect in the operation interface, so that the user can understand and operate more intuitively.

[0160] 102. Receive configuration parameters for the event from the user, and configure the event monitoring area in the operation interface according to the configuration parameters.

[0161] In an embodiment of the present invention, the configuration parameters include region type, region frame parameters, and event monitoring algorithm. The region type may be a shielding region / alarm region / protection region / contour analysis region / ROI region / AI analysis region, etc. The region frame parameters may be geometric attributes such as coordinates, size, and shape of the detection region. The event monitoring algorithm is used to identify specific events in the video, such as whether an object enters, leaves, or stays at a specific location in the monitoring area.

[0162] According to the area type, the monitoring algorithm corresponding to the area type can be matched in the event monitoring algorithm library, and according to the area frame parameters, the area frame can be drawn in three-dimensional space, and the event monitoring algorithm can be associated with the area frame, and the event monitoring area can be configured in the operation interface. The event monitoring algorithm can include shielded area monitoring algorithm / alarm area monitoring algorithm / protected area monitoring algorithm / contour analysis area monitoring algorithm / ROI area monitoring algorithm / AI analysis area monitoring algorithm, etc. Among them, the shielded area monitoring algorithm corresponds to the shielded area, the alarm area monitoring algorithm corresponds to the alarm area, the protected area monitoring algorithm corresponds to the protected area, the contour analysis area monitoring algorithm corresponds to the contour analysis area, the ROI area monitoring algorithm corresponds to the ROI area, and the AI ​​analysis area monitoring algorithm corresponds to the ROI area.

[0163] The above-mentioned event monitoring algorithm library may be a collection of multiple algorithms for detecting and identifying specific events.

[0164] It should be noted that the event monitoring algorithm is designed for different events. According to the area type, the algorithm that best matches different times can be selected from the time monitoring algorithm library. For example, if the area type is an alarm area or a protection area, an algorithm specifically used to monitor equipment failures or unsafe employee behavior will be selected; if the area type is an AI analysis area, an algorithm used to monitor crowd density or abnormal gathering behavior will be selected.

[0165] 103. Based on the configured event monitoring area and the point cloud data of the target area, event monitoring is performed on the event monitoring area.

[0166] In the embodiment of the present invention, the above-configured event monitoring area is used to monitor events within the area.

[0167] Event monitoring can be performed on the event monitoring area based on the configured event monitoring area and the point cloud data of the target area. The above event monitoring includes using event monitoring algorithms to analyze point cloud data, identify potential event signs, and generate corresponding alarms or reports. By performing event monitoring on the target event monitoring area, event activities in the target area can be monitored in real time, effectively improving the accuracy of target monitoring events.

[0168] In an embodiment of the present invention, point cloud data of a target area is received from a point cloud data acquisition device, and the target area is configured as a three-dimensional space for display in an operation interface; configuration parameters of an event from a user are received, and an event monitoring area is configured in the operation interface according to the configuration parameters, and the configuration parameters include area type, area frame parameters, and event monitoring algorithm; based on the configured event monitoring area and point cloud data of the target area, event monitoring is performed on the event monitoring area. The present invention receives point cloud data of a target area from a point cloud data acquisition device, and configures the target area as a three-dimensional space for display in an operation interface, receives configuration parameters of an event from a user, and configures the event monitoring area in the operation interface according to the configuration parameters, and uses the configured event monitoring area and point cloud data of the target area to perform event monitoring on the event monitoring area. The present invention introduces a combination of a host computer and a point cloud data acquisition device, as well as corresponding software algorithm support, to achieve three-dimensional spatial display and event monitoring of the target area, thereby improving the accuracy and flexibility of safety monitoring.

[0169] It is understandable that in the specific implementation of this application, point cloud data, configuration data, device data and other related data are involved. When the embodiments in this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0170] Optionally, in the step of configuring the event monitoring area in the operation interface according to the configuration parameters, the event monitoring algorithm corresponding to the area type can be matched in the event monitoring algorithm library according to the area type, and in the event monitoring algorithm library, different area types correspond to different event monitoring algorithms; according to the area frame parameters, a area frame is drawn in the three-dimensional space; the event monitoring algorithm is associated with the area frame, and the event monitoring area is configured in the operation interface.

[0171] In an embodiment of the present invention, the above-mentioned area types may be shielding area / alarm area / protection area / contour analysis area / ROI area / AI analysis area, etc.

[0172] The above event monitoring algorithm library can be understood as a set of algorithms for detecting and identifying specific events, and is used to analyze and identify different events. In the event monitoring algorithm library, different area types correspond to different event monitoring algorithms.

[0173] For example, if the area type is an alarm area, the alarm area intrusion detection is performed through the alarm area detection algorithm:

[0174] Step 1: Check whether there is a point cloud in the alarm area. If there is no point cloud, there is no intrusion IO output and no intrusion signal, otherwise proceed to the next step.

[0175] Step 2: Point cloud filtering processing. If there is no point cloud, there is no intrusion, and I0 outputs a no-intrusion signal, otherwise proceed to the next step.

[0176] Step 3: Point cloud clustering processing, calculate the object size (or number of points). If the object size or the maximum number of object points is less than the threshold, there is no intrusion, and the I / O output has no intrusion signal, otherwise proceed to the next step.

[0177] Step 4: If the intrusion exceeds M1 times for N consecutive samplings, the IO outputs the intrusion signal.

[0178] It should be noted that the event monitoring algorithm is designed for different events or behavior patterns, such as algorithms for equipment anomalies, object intrusions, personnel intrusions and other behaviors. According to the area type, the best matching algorithm is selected from the event monitoring algorithm library. Specifically, the event monitoring algorithm may include shielded area monitoring algorithm / alarm area monitoring algorithm / protected area monitoring algorithm / contour analysis area monitoring algorithm / ROI area monitoring algorithm / AI analysis area monitoring algorithm, etc. Among them, the shielded area monitoring algorithm corresponds to the shielded area, the alarm area monitoring algorithm corresponds to the alarm area, the protected area monitoring algorithm corresponds to the protected area, the contour analysis area monitoring algorithm corresponds to the contour analysis area, the ROI area monitoring algorithm corresponds to the ROI area, and the AI ​​analysis area monitoring algorithm corresponds to the ROI area.

[0179] The above-mentioned area frame parameters may be geometric attributes such as coordinates, size, shape, etc. of the detection area.

[0180] Specifically, the region frame can be drawn in three-dimensional space through the region frame parameters, such as position, size and shape; then, the event monitoring algorithm is associated with the region frame, and the event monitoring region can be configured in the operation interface through the association relationship between the event monitoring algorithm and the region frame. In this way, the monitored area and the events occurring in the area can be intuitively seen in the operation interface.

[0181] Optionally, the area frame parameters include frame length, frame width, and frame height. In the step of drawing the area frame in three-dimensional space according to the area frame parameters, the three-dimensional coordinates of the target positioning point can be determined in the three-dimensional space; the area frame is drawn in the three-dimensional space according to the frame length, frame width, frame height and the three-dimensional coordinate values ​​of the positioning point.

[0182] In the embodiment of the present invention, each target corresponds to a region frame. The above target may be a device such as a robot or a mechanical arm.

[0183] First, in the three-dimensional space, the three-dimensional coordinate position of the target positioning point in the three-dimensional space is determined; then, the area box is drawn in the three-dimensional space using the box length, box width, box height and the three-dimensional coordinate value of the positioning point. Each target corresponds to an area box, and these area boxes can be accurately located and drawn in the three-dimensional space.

[0184] Optionally, in the step of performing event monitoring on the event monitoring area based on the configured event monitoring area and the point cloud data of the target area, a user's selection instruction can be received to select at least one target event monitoring area from the configured event monitoring areas; and event monitoring is performed on the target event monitoring area based on the point cloud data of the target area and in combination with the event monitoring algorithm corresponding to the target event monitoring area.

[0185] In the embodiment of the present invention, the user's selection instruction may be a feature selection or operation made by the user in the system, such as clicking a button, selecting an option, etc.

[0186] In a possible embodiment, the user can click a button on the interface, select a drop-down menu option or other graphics. The user's selection instruction can be to click on a specific area mark, or to enter a specific area number or name. When the system receives the user's selection instruction, it will select at least one target event monitoring area from the configured event monitoring areas. The target event monitoring area can be a specific location that the user believes has a higher security risk or requires special attention. For each selected target event monitoring area, the point cloud data of the current target area can be used, combined with the event monitoring algorithm corresponding to the target event monitoring area, to perform event monitoring on the target event monitoring area.

[0187] Specifically, in the embodiment of the present invention, the area group can be understood as a set of areas composed of multiple event monitoring areas of the same area type, each area group corresponds to an event monitoring area of ​​one area type, and of course, multiple event monitoring areas of different area types can also be artificially combined into one area group. Areas within an area group can be increased or decreased through the area configuration module.

[0188] When receiving the regional group event switching signal, the corresponding regional group (event monitoring area) is switched according to the state of the IO. In the embodiment of the present invention, there are a total of four general IO input signals. There are three IOs with eight combinations of different levels input to each IO through the outside, corresponding to the events of eight regional groups. There is also an IO that is used as a parity check to count the number of high levels of the three pins IO1-3. Odd numbers need to set this IO to a high level, and even numbers to a low level.

[0189] For example, in the default state, these pins are not connected to signals. The selected event group (111-->7) counts the number of 1s in IO1-3. If the number is odd, the IO needs to be set to 1, and if the number is even, it is set to 0. IO4 is a check. In the event group (111-->7), IO1-3 are all 1, so the number of 1s is an odd number, so IO4 is set to 1. The selected event group (011-->3), in the event group (011-->3), the number of 1s in IO1-3 is 2, and the number of 0s is 1, that is, there is an IO that is 0, then the number of 1s is even, so IO4 is set to 0.

[0190] In one thread, four IO ports are polled and tested. IO4 verifies IO1-3. If the verification is successful, the value of IO1-3 is used as the currently selected event group. For example, (111-->7), the event group is the area group marked as 7. For example, (011-->3), the event group is the event group marked as 3.

[0191] Switching strategy:

[0192] The value input by the host computer or the external IO input is used as the current detection area group. Which method is used is through the configuration of a certain parameter. It can be understood that each event monitoring area has a number, and then the corresponding number is found through the value input by the host computer or the value input by the external IO to switch. Usually, the above 4 positions such as IO1-IO4 are used for switching.

[0193] Optionally, in the step of performing event monitoring on the event monitoring area based on the configured event monitoring area and the point cloud data of the target area, a switching instruction from the user can be received to determine the target event monitoring area in the event monitoring area; the current event monitoring area is switched to the target event monitoring area; and event monitoring is performed on the target event monitoring area based on the point cloud data of the target area and in combination with the event monitoring algorithm corresponding to the target event monitoring area.

[0194] In an embodiment of the present invention, after receiving a switching instruction from the user, the system will determine a target event monitoring area in the event monitoring area, which means that the system will adjust its monitoring focus according to the instruction to ensure that it pays attention to the key event area switched by the user.

[0195] The above-mentioned current event monitoring area can be understood as the area currently used to monitor a specific event. The above-mentioned target time monitoring area can be understood as the monitoring area expected to be achieved.

[0196] The above event detection algorithm is used to identify specific events in the video, such as whether an object enters, leaves or stays at a specific location in the monitoring area.

[0197] Furthermore, an event monitoring operation may be performed in the target event monitoring area based on the point cloud data of the target area and in combination with an event monitoring algorithm corresponding to the target event monitoring area.

[0198] The above-mentioned event monitoring includes using event monitoring algorithms to analyze point cloud data, identify potential event signs, and generate corresponding alarms or reports, etc. By performing event monitoring on the target event monitoring area, event activities in the target area can be monitored in real time, effectively improving the accuracy of target monitoring events.

[0199] In a possible embodiment, in the step of performing event monitoring on the event monitoring area based on the configured event monitoring area and the point cloud data of the target area, the monitoring activity of different area types in different time periods can be determined according to the monitoring results of the historical event monitoring area, and the target event monitoring areas for different time periods can be determined in the event monitoring area according to the monitoring activity in different time periods; when the corresponding time period is reached, the current event monitoring area is switched to the target event monitoring area for the corresponding time period; based on the point cloud data of the target area and in combination with the event monitoring algorithm corresponding to the target event monitoring area, event monitoring is performed on the target event monitoring area.

[0200] The above monitoring activity can be calculated by the following formula:

[0201]

[0202] Among them, the above r j represents the monitoring activity of a certain area type in the jth period, H represents the number of events corresponding to the area type detected in the jth period, and T i,j represents the duration of the event corresponding to the i-th event detected in the j-th time period, t i,j represents the start time of the event corresponding to the area type detected in the jth time period, t i-1,j G represents the start time of the event corresponding to the i-1th event detected in the jth time period, uot It indicates the number of times the event monitoring area corresponding to the area type is switched to by an external trigger switching instruction (a switching instruction input by the user) in the jth period. It can be seen that the monitoring activity increases with the increase of the duration of the event, the number of events detected, and the number of external trigger switching instructions, and increases with the decrease of the interval between two adjacent events detected.

[0203] The greater the above-mentioned monitoring activity, the better the monitoring effect of the event monitoring area corresponding to the area type. Therefore, the event monitoring area corresponding to the maximum monitoring activity in different time periods can be determined as the target event monitoring area for different time periods; when the corresponding time period is reached, the current event monitoring area is switched to the target event monitoring area for the corresponding time period.

[0204] Optionally, the area type includes at least one of a shielding area, a protection area, an alarm area, a contour analysis area, a focus area, and an AI analysis area. In the step of performing event monitoring on the event monitoring area based on the configured event monitoring area and the point cloud data of the target area, if the configured event monitoring area is a protection area or an alarm area, then based on each two-dimensional projection plane of the protection area or the alarm area, determine whether there is an intrusion event in the protection area or the alarm area; if there is an intrusion event in the protection area or the alarm area, output a first safety control signal; if the configured event monitoring area is a focus area, then based on the depth discrete rate of each point cloud in the focus area, determine the intrusion event in the focus area. Whether there is an intrusion event. If there is an intrusion event in the focus area, a second safety control signal is output; if the configured event monitoring area is a contour analysis area, based on the change in the distance between the reference frame point cloud data of the contour analysis area and each point cloud in the current frame point cloud data, it is determined whether there is a contour change event in the contour analysis area. If there is a contour change event in the contour analysis area, a third safety control signal is output; if the configured event monitoring area is an AI analysis area, based on the intensity image data and the three-dimensional point cloud data, it is determined whether there is a target person in the AI ​​analysis area. If there is a target person in the AI ​​analysis area, a fourth safety control signal is output.

[0205] In an embodiment of the present invention, taking a robot or a robotic arm as an example, the working area of ​​the robot or the robotic arm is a shielding area, and the area outside the shielding area is a protection area or an alarm area. When point cloud data appears in the protection area or the alarm area, it means that an object has invaded the protection area or the alarm area from the shielding area during the working process of the robot or the robotic arm, and a safety control signal can be output to the host computer or computer, thereby controlling the corresponding working equipment to stop working.

[0206] The above two-dimensional projection plane is the position of the three-dimensional point on the two-dimensional plane under the projection perspective.

[0207] If the configured event monitoring area is a protection area or an alarm area, it is determined whether there is an intrusion event in the protection area or the alarm area according to each two-dimensional projection plane of the protection area or the alarm area, and when there is an intrusion event in the protection area or the alarm area, a first security control signal is output. The first security control signal may be a prompt that there is a security threat and a requirement to take measures.

[0208] The above-mentioned area of ​​interest may be pre-defined according to the application, or may be a specific structure, etc.

[0209] The above depth discrete rate is used to indicate the fluctuation amplitude of the depth change of each point cloud in the focus area. The fluctuation amplitude is used to indicate the degree of change of the depth value in the focus area. If the depth discrete value is larger, the depth value in the focus area changes more drastically, that is, there is a large fluctuation; if the depth discrete value is smaller, it means that the depth value in the focus area changes more slowly, that is, the fluctuation amplitude is small.

[0210] If the configured event monitoring area is a focus area, then according to the depth discrete rate of each point cloud in the focus area, it is determined whether there is an intrusion event in the focus area, and when there is an intrusion event in the focus area, a second safety control signal is output. The second safety control signal may be to start an emergency safety measure.

[0211] The above-mentioned contour analysis area can be understood as the contour change area between the current frame and the reference frame. The current frame can be understood as a frame in the image sequence, or a frame captured by the sensor in real time. The reference frame is a predefined benchmark frame.

[0212] If the configured event monitoring area is a contour analysis area, then based on the distance change between the reference frame point cloud data of the contour analysis area and each point cloud in the current frame point cloud data, it is determined whether there is a contour change event in the contour analysis area. When there is a contour change event in the contour analysis area, a third safety control signal is output. The third safety control signal can be a specific signal issued to ensure operational safety, prevent potential risks, or respond to specific situations. Outputting the third safety control signal can indicate that a situation that requires special attention or action has been detected, but it may not have reached the severity level that requires a full shutdown or emergency braking.

[0213] The above-mentioned AI analysis area can be understood as the area obtained by performing target detection and segmentation on the intensity image data through the target detection model. The above-mentioned target detection model can be a target detection model built based on deep learning or machine learning, which can perform target detection on image data and identify the category and position of the object. The above-mentioned intensity image data can be understood as the intensity of the pixels of a single channel image. For example, in a grayscale image, it is the grayscale of the image, and in the RGB color space, it can be understood as the pixel grayscale value of the R, G, and B channels. The above-mentioned three-dimensional point cloud data is a collection of a large number of points distributed in a three-dimensional space, which is used to represent the surface or shape information of an object.

[0214] If the configured event monitoring area is an AI analysis area, then the intensity image data and the three-dimensional point cloud data are used to determine whether there is a target person in the AI ​​analysis area, and when there is a target person in the AI ​​analysis area, a fourth safety control signal is output. The fourth safety control signal can be a safety prompt for protecting the system or environment.

[0215] like Figure 2 As shown, an embodiment of the present invention provides a configuration device for a safety monitoring system, the safety monitoring system includes a host computer and at least one point cloud data acquisition device, the host computer includes an operation interface for interaction, the point cloud data acquisition device is used to collect point cloud data of a target area, and the configuration device of the safety monitoring system includes:

[0216] A first configuration module 201 is used to receive point cloud data of the target area from the point cloud data acquisition device, and configure the target area to be displayed in the operation interface as a three-dimensional space;

[0217] The second configuration module 202 is used to receive configuration parameters of the user for the event, and configure the event monitoring area in the operation interface according to the configuration parameters, wherein the configuration parameters include area type, area frame parameters and event monitoring algorithm;

[0218] The event monitoring module 203 is used to perform event monitoring on the event monitoring area based on the configured event monitoring area and the point cloud data of the target area.

[0219] Optionally, the second configuration module 202 is also used to match the event monitoring algorithm corresponding to the area type in the event monitoring algorithm library according to the area type, and in the event monitoring algorithm library, different area types correspond to different event monitoring algorithms; draw an area box in the three-dimensional space according to the area box parameters; associate the event monitoring algorithm with the area box, and configure the event monitoring area in the operation interface.

[0220] Optionally, the second configuration module 202 is also used to determine the three-dimensional coordinates of the target's positioning point in the three-dimensional space; draw an area box in the three-dimensional space according to the frame length, the frame width, the frame height and the three-dimensional coordinate value of the positioning point, and each target corresponds to one area box.

[0221] Optionally, the event monitoring module 203 is also used to receive a user's selection instruction, and select at least one target event monitoring area from the configured event monitoring areas; based on the point cloud data of the target area and in combination with the event monitoring algorithm corresponding to the target event monitoring area, perform event monitoring on the target event monitoring area.

[0222] Optionally, the event monitoring module 203 is also used to receive a switching instruction from the user, determine a target event monitoring area in the event monitoring area; switch the current event monitoring area to the target event monitoring area; and perform event monitoring on the target event monitoring area based on the point cloud data of the target area and in combination with the event monitoring algorithm corresponding to the target event monitoring area.

[0223] Optionally, the area type includes at least one of a shielding area, a protection area, an alarm area, a contour analysis area, a focus area, and an AI analysis area. The event monitoring module 203 is also used to determine whether there is an intrusion event in the protection area or the alarm area based on each two-dimensional projection plane of the protection area or the alarm area if the configured event monitoring area is a protection area or an alarm area, and if there is an intrusion event in the protection area or the alarm area, output a first safety control signal; if the configured event monitoring area is a focus area, determine whether there is an intrusion event in the focus area based on the depth discrete rate of each point cloud in the focus area, and if the focus area If there is an intrusion event in the area, a second security control signal is output; if the configured event monitoring area is a contour analysis area, based on the change in distance between the reference frame point cloud data of the contour analysis area and each point cloud in the current frame point cloud data, it is determined whether there is a contour change event in the contour analysis area, and if there is a contour change event in the contour analysis area, a third security control signal is output; if the configured event monitoring area is an AI analysis area, based on the intensity image data and the three-dimensional point cloud data, it is determined whether there is a target person in the AI ​​analysis area, and if there is a target person in the AI ​​analysis area, a fourth security control signal is output.

[0224] An embodiment of the present invention also provides a security monitoring system, which includes a host computer and at least one point cloud data acquisition device. The host computer includes an operating interface for interaction, the point cloud data acquisition device is used to collect point cloud data of the target area, and the host computer is used to execute the steps in the configuration method of the security monitoring system provided in the embodiment of the present invention.

[0225] like Figure 3 As shown, an embodiment of the present invention further provides an electronic device, including a processor, and the processor can execute any of the above-mentioned configuration methods of the security monitoring system.

[0226] Specifically, it includes a processor 301 and a memory 302, and a computer program for executing the configuration method of the safety monitoring system which is stored in the memory 302 and can be run on the processor 301, wherein:

[0227] The processor 301 runs the computer program of the configuration method of the safety monitoring system stored in the memory 302 to perform the following steps:

[0228] Receiving point cloud data of the target area from the point cloud data acquisition device, and configuring the target area to be displayed in the operation interface as a three-dimensional space;

[0229] Receiving configuration parameters for an event from a user, and configuring an event monitoring area in the operation interface according to the configuration parameters, wherein the configuration parameters include an area type, an area frame parameter, and an event monitoring algorithm;

[0230] Based on the configured event monitoring area and the point cloud data of the target area, event monitoring is performed on the event monitoring area.

[0231] Optionally, the configuring of the event monitoring area in the operation interface according to the configuration parameters performed by the processor 301 includes:

[0232] According to the area type, matching the event monitoring algorithm corresponding to the area type in the event monitoring algorithm library, wherein different area types correspond to different event monitoring algorithms in the event monitoring algorithm library;

[0233] Drawing an area frame in the three-dimensional space according to the area frame parameters;

[0234] The event monitoring algorithm is associated with the area frame, and an event monitoring area is configured in the operation interface.

[0235] Optionally, the region frame parameters include a frame length, a frame width, and a frame height, and the processor 301 draws a region frame in the three-dimensional space according to the region frame parameters, including:

[0236] In the three-dimensional space, determining the three-dimensional coordinates of the positioning point of the target;

[0237] According to the frame length, the frame width, the frame height and the three-dimensional coordinate values ​​of the positioning points, an area frame is drawn in the three-dimensional space, and each of the targets corresponds to one area frame.

[0238] Optionally, the processor 301 performs event monitoring on the event monitoring area based on the configured point cloud data of the event monitoring area and the target area, including:

[0239] receiving a selection instruction from a user, and selecting at least one target event monitoring area from among the configured event monitoring areas;

[0240] Based on the point cloud data of the target area and in combination with the event monitoring algorithm corresponding to the target event monitoring area, event monitoring is performed on the target event monitoring area.

[0241] Optionally, the processor 301 performs event monitoring on the event monitoring area based on the configured point cloud data of the event monitoring area and the target area, including:

[0242] receiving a switching instruction from a user, and determining a target event monitoring area in the event monitoring area;

[0243] Switching the current event monitoring area to the target event monitoring area;

[0244] Based on the point cloud data of the target area and in combination with the event monitoring algorithm corresponding to the target event monitoring area, event monitoring is performed on the target event monitoring area.

[0245] Optionally, the area type includes at least one of a shielding area, a protection area, an alarm area, a contour analysis area, a focus area, and an AI analysis area, and the processor 301 performs event monitoring on the event monitoring area based on the configured event monitoring area and the point cloud data of the target area, including:

[0246] If the configured event monitoring area is a protection area or an alarm area, determining whether there is an intrusion event in the protection area or the alarm area based on each two-dimensional projection plane of the protection area or the alarm area, and if there is an intrusion event in the protection area or the alarm area, outputting a first safety control signal;

[0247] If the configured event monitoring area is a focus area, determining whether there is an intrusion event in the focus area based on the depth discrete rate of each point cloud in the focus area, and outputting a second safety control signal if there is an intrusion event in the focus area;

[0248] If the configured event monitoring area is a contour analysis area, determining whether there is a contour change event in the contour analysis area based on the distance change between the reference frame point cloud data of the contour analysis area and each point cloud in the current frame point cloud data, and outputting a third safety control signal if there is a contour change event in the contour analysis area;

[0249] If the configured event monitoring area is an AI analysis area, it is determined whether there is a target person in the AI ​​analysis area based on the intensity image data and the three-dimensional point cloud data. If there is a target person in the AI ​​analysis area, a fourth safety control signal is output.

[0250] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the configuration method of the security monitoring system provided by the embodiment of the present invention are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0251] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0252] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for configuring a safety monitoring system, characterized in that: The safety monitoring system includes a host computer and at least one point cloud data acquisition device, the host computer includes an operation interface for interaction, the point cloud data acquisition device is used to collect point cloud data of the target area, and the method includes the following steps: Receiving point cloud data of the target area from the point cloud data acquisition device, and configuring the target area to be displayed in the operation interface as a three-dimensional space; Receiving configuration parameters for an event from a user, and configuring an event monitoring area in the operation interface according to the configuration parameters, wherein the configuration parameters include an area type, an area frame parameter, and an event monitoring algorithm; Based on the configured event monitoring area and the point cloud data of the target area, event monitoring is performed on the event monitoring area.

2. The method for configuring a safety monitoring system according to claim 1, characterized in that: The configuring the event monitoring area in the operation interface according to the configuration parameters includes: According to the area type, matching the event monitoring algorithm corresponding to the area type in the event monitoring algorithm library, wherein different area types correspond to different event monitoring algorithms in the event monitoring algorithm library; Drawing an area frame in the three-dimensional space according to the area frame parameters; The event monitoring algorithm is associated with the area frame, and an event monitoring area is configured in the operation interface.

3. The configuration method of the safety monitoring system according to claim 2, characterized in that: The area frame parameters include a frame length, a frame width, and a frame height, and drawing an area frame in the three-dimensional space according to the area frame parameters includes: In the three-dimensional space, determining the three-dimensional coordinates of the positioning point of the target; According to the frame length, the frame width, the frame height and the three-dimensional coordinate values ​​of the positioning points, an area frame is drawn in the three-dimensional space, and each of the targets corresponds to one area frame.

4. The method for configuring a safety monitoring system according to claim 2, wherein: The performing event monitoring on the event monitoring area based on the configured point cloud data of the event monitoring area and the target area includes: receiving a selection instruction from a user, and selecting at least one target event monitoring area from among the configured event monitoring areas; Based on the point cloud data of the target area and in combination with the event monitoring algorithm corresponding to the target event monitoring area, event monitoring is performed on the target event monitoring area.

5. The method for configuring a safety monitoring system according to claim 2, wherein: The performing event monitoring on the event monitoring area based on the configured point cloud data of the event monitoring area and the target area includes: receiving a switching instruction from a user, and determining a target event monitoring area in the event monitoring area; Switching the current event monitoring area to the target event monitoring area; Based on the point cloud data of the target area and in combination with the event monitoring algorithm corresponding to the target event monitoring area, event monitoring is performed on the target event monitoring area.

6. The method for configuring a safety monitoring system according to claim 1, characterized in that: The area type includes at least one of a shielding area, a protection area, an alarm area, a contour analysis area, a focus area, and an AI analysis area. The event monitoring of the event monitoring area based on the configured point cloud data of the event monitoring area and the target area includes: If the configured event monitoring area is a protection area or an alarm area, determining whether there is an intrusion event in the protection area or the alarm area based on each two-dimensional projection plane of the protection area or the alarm area, and if there is an intrusion event in the protection area or the alarm area, outputting a first safety control signal; If the configured event monitoring area is a focus area, determining whether there is an intrusion event in the focus area based on the depth discrete rate of each point cloud in the focus area, and outputting a second safety control signal if there is an intrusion event in the focus area; If the configured event monitoring area is a contour analysis area, determining whether there is a contour change event in the contour analysis area based on the distance change between the reference frame point cloud data of the contour analysis area and each point cloud in the current frame point cloud data, and outputting a third safety control signal if there is a contour change event in the contour analysis area; If the configured event monitoring area is an AI analysis area, it is determined whether there is a target person in the AI ​​analysis area based on the intensity image data and the three-dimensional point cloud data. If there is a target person in the AI ​​analysis area, a fourth safety control signal is output.

7. A configuration device for a safety monitoring system, the safety monitoring system comprising a host computer and at least one point cloud data acquisition device, the host computer comprising an operation interface for interaction, the point cloud data acquisition device for acquiring point cloud data of a target area, the device comprising: A first configuration module is used to receive point cloud data of the target area from the point cloud data acquisition device, and configure the target area to be displayed in the operation interface as a three-dimensional space; A second configuration module, used to receive configuration parameters for an event from a user, and configure an event monitoring area in the operation interface according to the configuration parameters, wherein the configuration parameters include an area type, an area frame parameter, and an event monitoring algorithm; The event monitoring module is used to perform event monitoring on the event monitoring area based on the configured point cloud data of the event monitoring area and the target area.

8. A safety monitoring system, characterized in that: The safety monitoring system includes a host computer and at least one point cloud data acquisition device, the host computer includes an operation interface for interaction, the point cloud data acquisition device is used to collect point cloud data of the target area, and the host computer is used to execute the steps in the configuration method of the safety monitoring system as described in any one of claims 1 to 6.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps in the method for configuring a safety monitoring system according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the method for configuring a safety monitoring system according to any one of claims 1 to 6 are implemented.

Images