Measurable infrared camera monitoring system based on stereo distance measurement

Abstract

The invention relates to the technical field of wild animal monitoring, in particular to a measurable infrared camera monitoring system based on stereoscopic distance measurement, which identifies a target through an infrared monitoring device, and obtains images of the target respectively by using a binocular distance measurement device when the target is identified to enter a monitorable area; a radar ranging device is used for determining the distance between a camera and a target, feature points of two target images are obtained respectively, the corresponding feature points are marked as feature point pairs, depth information of the target is determined according to the relation between the feature point pairs, and the depth information reflects the distance between each point on the target and the ranging device. The characteristics of continuity, smoothness and the like of the contour line can help to optimize the acquisition of depth information, so that the monitoring target is further analyzed according to the image information and the contour line, the analysis accuracy of the information of the monitoring target is improved, and the analysis efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wild animal monitoring, and in particular to a measurable infrared camera monitoring system based on stereo ranging. Background Art

[0002] Wild animals are an important part of the ecosystem. By monitoring the number, distribution and behavior of wild animals, we can gain a deep understanding of the structure and function of the ecosystem. Existing technologies use real-time transmission of thermal imaging signals of wild animals and real-time tracking and shooting signals by infrared cameras, and provide airbags to seal the monitoring module to prevent damage to the system body caused by complex outdoor weather. However, there is a lack of monitoring technology for the size of animals, and the size of the monitored animals is mostly determined manually, resulting in low analysis efficiency and insufficient analysis accuracy.

[0003] Chinese patent application number: CN202310188708.3 discloses a wildlife dynamic monitoring and feedback system based on an infrared camera, including: a monitoring module, a power module, a solar power generation module, and a communication module. The monitoring module is used for real-time monitoring of wildlife, and includes a box body, an infrared camera and a thermal imaging camera arranged in parallel on the front end face of the box body, and the infrared camera includes a camera seat and an infrared camera; the power module is used to drive the infrared camera to extend and retract relative to the front end face of the box body, and the power module includes an air pump, a transmission component connected to the air pump, and a pressure relief valve arranged on the pipeline connecting the air pump and the transmission component; the monitoring feedback system provided by the present invention can transmit the thermal imaging signal of wild animals and the real-time tracking and shooting signal of the infrared camera in real time, and the arrangement of the first airbag and the second airbag can achieve sealing of the monitoring module under various working conditions of the infrared camera to prevent damage to the system body due to complex outdoor weather conditions.

[0004] However, the prior art still has the following problems:

[0005] There is a lack of monitoring technology for the size of animals, and the size of the monitored animals is mostly determined manually, resulting in low analysis efficiency and insufficient analysis accuracy. Summary of the invention

[0006] To this end, the present invention provides a measurable infrared camera monitoring system based on stereo ranging to overcome the problem that the existing technology for monitoring the size of animals is relatively scarce, mostly relies on manual determination of the size of the monitored animals, and has low analysis efficiency and insufficient analysis accuracy.

[0007] To achieve the above-mentioned purpose, the present invention provides a measurable infrared camera monitoring system based on stereo ranging. It includes:

[0008] An infrared monitoring module, which is used to send out a monitoring signal when a target to be monitored is identified;

[0009] A radar ranging module, which is connected to the infrared monitoring module and is used to detect the detection distance between the target to be monitored and the camera;

[0010] A depth image acquisition module, comprising a first acquisition device for acquiring a first image and a second acquisition device for acquiring a second image, for acquiring an image of a target to be monitored;

[0011] A data processing module, connected to the depth image acquisition module, for extracting feature points based on the image acquired by the depth image acquisition module, and determining the depth information of the target to be monitored based on the extracted feature points;

[0012] an analysis module, which is respectively connected to the infrared monitoring module, the radar ranging module, the depth image acquisition module and the data processing module, and is used to analyze whether the acquired image is a target to be calculated based on the depth information of the target to be monitored and the length of the contour line in the image of the target to be monitored, and to make a secondary judgment on whether the acquired image is a target to be calculated based on historical image information when the acquired image is initially determined to be not a target to be calculated, or to analyze the reason why the acquired image is not a target to be calculated based on the distance between each pair of feature points;

[0013] A storage module is connected to the analysis module and is used to store image information.

[0014] Furthermore, the data processing module is used to perform pairing processing on corresponding feature points in the first feature point group and the second feature point group to obtain a plurality of feature point pairs, and to determine the depth information of the target to be monitored based on the distance between each feature point pair.

[0015] The first feature point group is determined based on the first image, and the second feature point group is determined based on the second image.

[0016] Further, the analysis module is used to calculate the depth mean corresponding to each pair of feature points of the target to be monitored, and calculate the ratio of the depth mean to the length of the contour line of the target to be monitored in the image, so as to analyze whether the acquired image is the target to be calculated according to the ratio, including:

[0017] When determining that the acquired image is a target to be calculated, entering the image information into the storage module;

[0018] When the image is initially determined to be a non-target to be calculated, a secondary determination is made based on historical image information to determine whether the image is a target to be calculated.

[0019] Or, it is determined that the acquired image is not the target to be calculated, and the reason why the acquired image is not the target to be calculated is analyzed based on the distance between each pair of feature points.

[0020] Furthermore, the analysis module is also used to determine the depth mean calculated at each time node in the historical image information, and the length of the contour line of the target to be monitored in the corresponding image, and calculate the ratio of each depth mean to the length of the contour line, and calculate the variance of each ratio to perform a secondary determination on whether the acquired image is the target to be calculated based on the variance, including:

[0021] When determining that the acquired image is not the target to be calculated, analyzing the reason why the acquired image is not the target to be calculated based on the distance between each pair of feature points;

[0022] When it is determined that the target to be monitored is in a moving state, contour features of the target to be monitored in the image are acquired, and the direction of the target to be monitored is determined based on the contour features.

[0023] Furthermore, the analysis module is also used to adjust the preset standard interval range based on the determined angle between the orientation of the target to be monitored and the direction facing the camera, wherein the expansion amount of the preset standard interval range is negatively correlated with the angle.

[0024] Furthermore, the analysis module is also used to calculate the average value of the distances between the feature point pairs to obtain a distance mean, and analyze the reasons why the acquired image is not the target to be calculated based on the distance mean, including:

[0025] The reason for determining that the acquired image is not the target to be calculated is the environmental influence;

[0026] The analysis module determines the reason why the acquired image is not the target to be calculated based on the mean value of each distance in the historical data, and makes a secondary determination.

[0027] Or, the reason for determining that the acquired image is not the target to be calculated is that the acquisition is unqualified.

[0028] Furthermore, the analysis module is also used to correct the noise reduction factor based on the ambient brightness under the condition of environmental influence, wherein the increase in the noise reduction factor is positively correlated with the ambient brightness.

[0029] Furthermore, the analysis module is also used to calculate the distance variance of each distance mean in the historical data, and based on the distance variance, secondarily determine the reason why the acquired image is not the target to be calculated, including:

[0030] The reason for determining that the acquired image is not the target to be calculated is the environmental influence.

[0031] Or, the reason why the acquired image is determined to be a non-target to be calculated is that the detection distance does not match the camera position.

[0032] Furthermore, the analysis module is also used to adjust the distance between the first acquisition device and the second acquisition device based on the detection distance, wherein the increase in the distance is positively correlated with the detection distance.

[0033] Furthermore, the analysis module is also used to adjust the detection sensitivity based on the ambient temperature when the acquisition is determined to be unqualified, wherein the reduction in the detection sensitivity is negatively correlated with the ambient temperature.

[0034] Compared with the prior art, the beneficial effect of the present invention lies in that, in the present invention, a target is identified by an infrared monitoring device, and when the target is identified to enter a monitorable area, a binocular ranging device is used to respectively obtain images of the target, a radar ranging device is used to determine the distance between the camera and the target, and feature points of the two target images are respectively obtained, and the corresponding feature points are marked as feature point pairs, and the depth information of the target is determined according to the relationship between each feature point pair. The depth information reflects the distance between each point on the target and the ranging device. Considering the continuity and smoothness of the contour line and other features, it can help optimize the acquisition of depth information, and thus the monitoring target is further analyzed according to the image information and the contour line, thereby improving the analysis accuracy of the monitoring target information, and further determining the volume information of the target according to the acquired depth information of the target, avoiding artificial determination of the target volume, and avoiding errors caused by artificial determination of the volume information, thereby unifying the analysis process parameters and improving the analysis efficiency.

[0035] Furthermore, the present invention takes into account that the clarity of the target contour line in the acquired target image has a great influence on the depth information of the determined target. For example, the tail of an animal is blocked by the body or the legs block each other. Such occlusion will cause part of the depth information and contour information to be missing, affecting the accurate estimation of the volume. Therefore, the accuracy of the determined depth information is further analyzed based on the degree of fluctuation of the depth information calculated at each feature point, thereby improving the accuracy of the analysis of the target information.

[0036] Furthermore, the present invention takes into account that during the image acquisition process, the ambient brightness will have a great impact on the image information. If there is an exposure phenomenon, the contour line of the identified target will be inaccurate, affecting the analysis accuracy. Therefore, the noise reduction factor is adjusted according to the ambient brightness, thereby improving the control accuracy of the image acquisition process, and then improving the analysis accuracy of the target depth information.

[0037] Furthermore, the present invention takes into account that the greater the distance between feature points, the higher the accuracy of the depth information, because a larger feature point spacing can provide a more obvious parallax change, thereby more accurately calculating the depth. Therefore, the depth information of the target is analyzed according to the fluctuation of the distance value between each feature point, thereby improving the accuracy of the analysis of the depth information of the target. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic structural diagram of a measurable infrared camera monitoring system based on stereo ranging of the present invention;

[0039] Figure 2 A flow chart for determining whether the image acquired by the analysis is the target to be calculated;

[0040] Figure 3 A flow chart for determining whether the acquired image is a target to be calculated for secondary determination;

[0041] Figure 4 A flow chart for determining why the image acquired for analysis is not the target to be calculated;

[0042] In the figure: 1-infrared monitoring camera; 2-first acquisition device; 3-second acquisition device; 4-radar ranging module; 5-infrared monitoring module; 6-wireless transmission device; 7-GNSS positioning device. DETAILED DESCRIPTION

[0043] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] It should be pointed out that the data in this embodiment are obtained by comprehensive analysis and evaluation of the historical data of the system of the present invention in the six months before this determination and the corresponding historical determination results. It can be understood by those skilled in the art that the determination method of the system of the present invention for a single parameter mentioned above can be to select the value with the highest proportion as the preset standard parameter according to the data distribution, use weighted summation to use the obtained value as the preset standard parameter, substitute each historical data into a specific formula and use the value obtained by the formula as the preset standard parameter or other selection methods, as long as the system of the present invention can clearly define different specific situations in the single determination process through the obtained values.

[0045] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0046] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0047] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0048] See also Figure 1 As shown, it is a schematic structural diagram of a measurable infrared camera monitoring system based on stereo ranging of the present invention.

[0049] This embodiment provides a scalable infrared camera monitoring system based on stereo ranging, including:

[0050] An infrared monitoring module, which is used to send out a monitoring signal when a target to be monitored is identified;

[0051] A radar ranging module, which is connected to the infrared monitoring module and is used to detect the detection distance between the target to be monitored and the camera;

[0052] A depth image acquisition module, comprising a first acquisition device for acquiring a first image and a second acquisition device for acquiring a second image, for acquiring an image of a target to be monitored;

[0053] A data processing module, connected to the depth image acquisition module, for extracting feature points based on the image acquired by the depth image acquisition module, and determining the depth information of the target to be monitored based on the extracted feature points;

[0054] an analysis module, which is respectively connected to the infrared monitoring module, the radar ranging module, the depth image acquisition module and the data processing module, and is used to analyze whether the acquired image is a target to be calculated based on the depth information of the target to be monitored and the length of the contour line in the image of the target to be monitored, and to make a secondary judgment on whether the acquired image is a target to be calculated based on historical image information when the acquired image is initially determined to be not a target to be calculated, or to analyze the reason why the acquired image is not a target to be calculated based on the distance between each pair of feature points;

[0055] A storage module is connected to the analysis module and is used to store image information.

[0056] Specifically, in this embodiment, the specific structures of the infrared monitoring module and the radar ranging module are not limited. The infrared monitoring module can use an infrared sensor or an infrared detector, and the radar ranging module can use a pulse radar ranging device or a continuous wave radar ranging device, which belongs to the existing technology and will not be repeated here.

[0057] Specifically, in this embodiment, the specific structure of the depth image acquisition module is not limited, and it only needs to be able to realize the corresponding function. A binocular vision camera can be used, which belongs to the existing technology and will not be repeated here.

[0058] Specifically, in this embodiment, the specific structures of the analysis module and the storage module are not limited, and they can be composed of logic components, and the logic components include a field programmable processor, a computer, and a microprocessor in the computer.

[0059] In the present invention, a target is identified by an infrared monitoring device. When the target is identified to enter a monitorable area, a binocular distance measuring device is used to respectively obtain images of the target, a radar distance measuring device is used to determine the distance between a camera and the target, feature points of the two target images are respectively obtained, and the corresponding feature points are marked as feature point pairs. According to the relationship between each feature point pair, the depth information of the target is determined. The depth information reflects the distance between each point on the target and the distance measuring device. Considering the characteristics such as the continuity and smoothness of the contour line, it can help optimize the acquisition of the depth information. Therefore, the monitoring target is further analyzed according to the image information and the contour line, thereby improving the analysis accuracy of the monitoring target information. According to the acquired depth information of the target, the volume information of the target is further determined, and the target volume is avoided to be determined artificially, and the error caused by the artificial determination of the volume information is avoided, thereby unifying the analysis process parameters and improving the analysis efficiency.

[0060] Specifically, the data processing module is used to perform pairing processing on the corresponding feature points in the first feature point group and the second feature point group to obtain a plurality of feature point pairs, and to determine the depth information of the target to be monitored based on the distance between each feature point pair.

[0061] The first feature point group is determined based on the first image, and the second feature point group is determined based on the second image.

[0062] Specifically, in this embodiment, determining the depth information of the target to be monitored based on the feature point pairs belongs to the existing technology. For example, the extracted feature points can be matched, the parallax can be calculated, and the depth information of the target to be monitored can be calculated based on the triangulation principle, which will not be repeated here.

[0063] See also Figure 2 As shown, it is a flow chart for determining whether the acquired image is the target to be calculated.

[0064] Specifically, the analysis module is used to calculate the depth mean corresponding to each pair of feature points of the target to be monitored, and calculate the ratio of the depth mean to the length of the contour line of the target to be monitored in the image, so as to analyze whether the acquired image is the target to be calculated according to the ratio, including:

[0065] If the ratio is within the first preset standard interval, the analysis module determines that the acquired image is a target to be calculated, and enters the image information into the storage module;

[0066] If the ratio is within the second preset standard interval, the analysis module preliminarily determines that the acquired image is not a target to be calculated, and performs a secondary determination on whether the acquired image is a target to be calculated based on historical image information;

[0067] If the ratio is within a third preset standard interval, the analysis module determines that the acquired image is a non-target to be calculated, and analyzes the reason why the acquired image is a non-target to be calculated based on the distance between each pair of feature points.

[0068] Specifically, in this embodiment, the first preset standard interval is obtained by pre-measurement, and the body shape information data of the same type of target as the current monitored target is obtained, images of each target at each angle are obtained, feature points are determined and the depth of each feature point is obtained respectively, the depth mean of each feature point is calculated, the ratio of the depth mean to the length of the contour line in the corresponding image is calculated, and the single-angle body shape ratio is obtained, the average value of the single-angle body shape ratios of the images of a single target at each angle is calculated to obtain the body shape ratio of a single target, the body shape ratios of several targets of the same type are calculated, the number of body shape ratios is counted, and the body shape ratio with the largest number is recorded as the body shape ratio standard. The first preset standard interval is [0.9×body shape ratio standard, 1.2×body shape ratio standard], the second preset standard interval is [0.85×body shape ratio standard, 0.9×body shape ratio standard) or (1.2×body shape ratio standard, 1.3×body shape ratio standard], and the third preset standard interval is a range that is neither the first preset standard interval nor the second preset standard interval.

[0069] See also Figure 3 As shown, it is a flow chart for determining whether the acquired image is the target to be calculated for the second time.

[0070] Specifically, the analysis module is also used to determine the depth mean calculated at each time node in the historical image information, and the length of the contour line of the target to be monitored in the corresponding image, and calculate the ratio of each depth mean to the length of the contour line, and calculate the variance of each ratio to perform a secondary determination on whether the acquired image is the target to be calculated based on the variance, including:

[0071] If the variance is less than or equal to a preset variance standard threshold, the analysis module determines that the acquired image is a non-target to be calculated, and analyzes the reason why the acquired image is a non-target to be calculated based on the distance between each pair of feature points;

[0072] If the variance is greater than the preset variance standard threshold, the analysis module determines that the target to be monitored is in a moving state, obtains contour features of the target to be monitored in the image, and determines the direction of the target to be monitored based on the contour features.

[0073] Specifically, in this embodiment, the preset variance standard threshold is obtained by pre-determining the single-angle body size ratio of a single target of the same type as the current monitored target, calculating the variance of the single-angle body size ratio of each angle image, and calculating the mean variance of the single-angle body size ratios of several targets of the same type to obtain the preset variance standard threshold.

[0074] The present invention takes into account that the clarity of the target contour line in the acquired target image has a great influence on the determined depth information of the target. For example, the tail of an animal is blocked by the body or the legs block each other. Such occlusion will cause partial loss of depth information and contour information, affecting the accurate estimation of the volume. Therefore, the accuracy of the determined depth information is further analyzed based on the degree of fluctuation of the depth information calculated at each feature point, thereby improving the accuracy of the analysis of the target information.

[0075] Specifically, the analysis module is further used to adjust the preset standard interval range based on the determined angle between the orientation of the target to be monitored and the direction facing the camera, wherein the expansion amount of the preset standard interval range is negatively correlated with the angle.

[0076] In this embodiment, optionally,

[0077] The angle is compared with the first preset angle standard threshold and the second preset angle standard threshold,

[0078] If the angle is less than or equal to the first preset angle standard threshold, the first preset standard interval range is expanded by the first interval range, and the expanded range is expanded to the left and right ends of the first preset standard interval range by 0.04×body size ratio standard units respectively;

[0079] If the angle is greater than the first preset angle standard threshold and less than or equal to the second preset angle standard threshold, the first preset standard interval range is expanded to the second interval range, and the expanded range is expanded to the left and right ends of the first preset standard interval range by 0.03×body size ratio standard units respectively;

[0080] If the angle is greater than the second preset angle standard threshold, the first preset standard interval is expanded to a third interval, and the expanded range is expanded to 0.02×body size ratio standard units to the left and right ends of the first preset standard interval respectively;

[0081] Among them, the second preset standard interval range is reduced by a corresponding number of units.

[0082] Specifically, in this embodiment, when the preset standard interval is adjusted, re-analyzing whether the acquired image is the target to be calculated based on the ratio of the depth mean value to the length of the contour line of the target to be monitored in the image includes:

[0083] If the ratio is within the adjusted first preset standard interval, the acquired image is determined to be a target to be calculated, and the image information is recorded into the storage module;

[0084] If the ratio is outside the adjusted first preset standard interval, the acquired image is determined to be a non-target to be calculated, and the reason why the acquired image is a non-target to be calculated is analyzed based on the distance between each pair of feature points.

[0085] See also Figure 4 As shown, it is a flow chart for determining the reason why the image acquired by analysis is not the target to be calculated.

[0086] Specifically, the analysis module is further used to calculate the average value of the distances between the feature point pairs to obtain a distance mean, and analyze the reasons why the acquired image is not the target to be calculated based on the distance mean, including:

[0087] If the distance mean is less than or equal to the first preset distance mean standard threshold, the reason why the analysis module determines that the acquired image is not the target to be calculated is environmental influence;

[0088] If the distance mean is greater than the first preset distance mean standard threshold and less than or equal to the second preset distance mean standard threshold, the analysis module determines to perform a secondary determination based on the distance means in the historical data on why the acquired image is not a target to be calculated;

[0089] If the distance mean is greater than the second preset distance mean standard threshold, the reason why the analysis module determines that the acquired image is not the target to be calculated is that the acquisition is unqualified.

[0090] Specifically, in this embodiment, the first preset distance mean standard threshold and the second preset distance mean standard threshold are obtained in advance, and a number of target images that meet the target depth prediction requirements are obtained, the distance between each feature point is calculated, and the distance mean is solved. The first preset distance mean standard threshold is 0.85 to 1.05 times the distance mean, and the second preset distance mean standard threshold is 1.1 to 1.2 times the distance mean.

[0091] Specifically, the analysis module is further configured to correct the noise reduction factor based on the ambient brightness under the condition of environmental influence, wherein the increase in the noise reduction factor is positively correlated with the ambient brightness.

[0092] In this embodiment, optionally,

[0093] The ambient brightness is compared with the first preset ambient brightness standard threshold and the second preset ambient brightness standard threshold,

[0094] If the ambient brightness is less than or equal to the first preset ambient brightness standard threshold, increase the first noise reduction ratio, which is 0.1 times the initial noise reduction ratio;

[0095] If the ambient brightness is greater than the first preset ambient brightness standard threshold and less than or equal to the second preset ambient brightness standard threshold, then increase the second noise reduction ratio, which is 0.2 times the initial noise reduction ratio;

[0096] If the ambient brightness is greater than the second preset ambient brightness standard threshold, the third noise reduction ratio is increased, and the third noise reduction ratio is 0.25 times the initial noise reduction ratio;

[0097] Among them, the first preset ambient brightness standard threshold and the second preset ambient brightness standard threshold are obtained in advance, and the optimal ambient brightness for capturing the target image is determined based on big data. The first preset ambient brightness standard threshold is 0.9 times the optimal ambient brightness, and the second preset ambient brightness standard threshold is 1.2 times the optimal ambient brightness.

[0098] The present invention takes into account that during the image acquisition process, the ambient brightness will have a great impact on the image information. If there is an exposure phenomenon, the contour line of the identified target will be inaccurate, affecting the analysis accuracy. Therefore, the noise reduction factor is adjusted according to the ambient brightness, thereby improving the control accuracy of the image acquisition process, and further improving the analysis accuracy of the target depth information.

[0099] Specifically, the analysis module is further used to calculate the distance variance of each distance mean in the historical data, and based on the distance variance, secondarily determine the reason why the acquired image is not the target to be calculated, including:

[0100] If the distance variance is less than or equal to a preset distance variance standard threshold, the reason why the analysis module determines that the acquired image is not a target to be calculated is due to environmental influence;

[0101] If the distance variance is greater than the preset distance variance standard threshold, the reason why the analysis module determines that the acquired image is not a target to be calculated is that the detection distance does not match the camera position.

[0102] Specifically, in this embodiment, the preset distance variance standard threshold is obtained by pre-measurement, obtaining a number of qualified images for depth prediction of the target image, determining the distance between each feature point, solving the variance of each distance, and obtaining the preset distance variance standard threshold.

[0103] The present invention takes into account that the greater the distance between feature points, the higher the accuracy of the depth information, because a larger feature point spacing can provide a more obvious parallax change, thereby more accurately calculating the depth. Therefore, the depth information of the target is analyzed according to the fluctuation of the distance value between each feature point, thereby improving the accuracy of the analysis of the depth information of the target.

[0104] Specifically, the analysis module is further used to adjust the distance between the first acquisition device and the second acquisition device based on the detection distance, wherein the increase in the distance is positively correlated with the detection distance.

[0105] In this embodiment, optionally,

[0106] The detection distance is compared with the first preset detection distance standard threshold and the second preset detection distance standard threshold,

[0107] If the detection distance is less than or equal to the first preset detection distance standard threshold, the first spacing is increased, and the first spacing is 0.1 times the initial spacing;

[0108] If the detection distance is greater than the first preset detection distance standard threshold and less than or equal to the second preset detection distance standard threshold, then increase the second spacing, and the second spacing is 0.2 times the initial spacing;

[0109] If the detection distance is greater than the second preset detection distance standard threshold, the third distance is increased, and the third distance is 0.3 times the initial distance;

[0110] Among them, the first preset detection distance standard threshold and the second preset detection distance standard threshold are obtained in advance, and the optimal detection distance for obtaining the monitoring target is determined based on big data. The first preset detection distance standard threshold is 1.15 times the optimal detection distance, and the second preset detection distance standard threshold is 1.25 times the optimal detection distance.

[0111] Specifically, the analysis module is further configured to adjust the detection sensitivity based on the ambient temperature when the acquisition is determined to be unqualified, wherein the reduction in the detection sensitivity is negatively correlated with the ambient temperature.

[0112] In this embodiment, optionally,

[0113] The ambient temperature is compared with the first preset ambient temperature and the second preset ambient temperature.

[0114] If the ambient temperature is less than or equal to the first preset ambient temperature standard threshold, the first detection sensitivity is reduced, and the first detection sensitivity is 0.2 times the initial detection sensitivity;

[0115] If the ambient temperature is greater than the first preset ambient temperature standard threshold and less than or equal to the second preset ambient temperature standard threshold, the second detection sensitivity is reduced, and the second detection sensitivity is 0.15 times the initial sensitivity;

[0116] If the ambient temperature is greater than the second preset ambient temperature standard threshold, the third detection sensitivity is reduced, and the third detection sensitivity is 0.1 times the initial sensitivity;

[0117] Among them, the first preset ambient temperature standard threshold and the second preset ambient temperature standard threshold are obtained in advance, and the optimal ambient temperature during the use of the infrared monitoring device is determined based on big data. The first preset ambient temperature standard threshold is 1.2 times the optimal ambient temperature, and the second preset ambient temperature standard threshold is 1.3 times the optimal ambient temperature.

[0118] Specifically, in this embodiment, an adjustment knob is usually set on the device or there are adjustable resistors and other components in the internal circuit. For example, by rotating a potentiometer to change the resistance value in the circuit, the gain of the signal amplification circuit is changed, thereby changing the detection sensitivity of the infrared monitoring device. This belongs to the prior art and will not be elaborated here.

[0119] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0120] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A scalable infrared camera monitoring system based on stereo ranging, characterized in that: include: An infrared monitoring module, which is used to send out a monitoring signal when a target to be monitored is identified; A radar ranging module, which is connected to the infrared monitoring module and is used to detect the detection distance between the target to be monitored and the camera; A depth image acquisition module, comprising a first acquisition device for acquiring a first image and a second acquisition device for acquiring a second image, for acquiring an image of a target to be monitored; A data processing module, connected to the depth image acquisition module, for extracting feature points based on the image acquired by the depth image acquisition module, and determining the depth information of the target to be monitored based on the extracted feature points; an analysis module, which is respectively connected to the infrared monitoring module, the radar ranging module, the depth image acquisition module and the data processing module, and is used to analyze whether the acquired image is a target to be calculated based on the depth information of the target to be monitored and the length of the contour line in the image of the target to be monitored, and to make a secondary judgment on whether the acquired image is a target to be calculated based on historical image information when the acquired image is initially determined to be not a target to be calculated, or to analyze the reason why the acquired image is not a target to be calculated based on the distance between each pair of feature points; A storage module is connected to the analysis module and is used to store image information.

2. The scalable infrared camera monitoring system based on stereo ranging according to claim 1 is characterized in that: The data processing module is used to perform pairing processing on the corresponding feature points in the first feature point group and the second feature point group to obtain a plurality of feature point pairs, and to determine the depth information of the target to be monitored based on the distance between each feature point pair. The first feature point group is determined based on the first image, and the second feature point group is determined based on the second image.

3. The scalable infrared camera monitoring system based on stereo ranging according to claim 1 is characterized in that: The analysis module is used to calculate the depth mean corresponding to each pair of feature points of the target to be monitored, and calculate the ratio of the depth mean to the length of the contour line of the target to be monitored in the image, so as to analyze whether the acquired image is the target to be calculated according to the ratio, including: When determining that the acquired image is a target to be calculated, entering the image information into the storage module; When the image is initially determined to be a non-target to be calculated, a secondary determination is made based on historical image information to determine whether the image is a target to be calculated. Or, it is determined that the acquired image is not the target to be calculated, and the reason why the acquired image is not the target to be calculated is analyzed based on the distance between each pair of feature points.

4. The scalable infrared camera monitoring system based on stereo ranging according to claim 3 is characterized in that: The analysis module is also used to determine the depth mean calculated at each time node in the historical image information, and the length of the contour line of the target to be monitored in the corresponding image, and calculate the ratio of each depth mean to the length of the contour line, and calculate the variance of each ratio to perform a secondary determination on whether the acquired image is the target to be calculated based on the variance, including: When determining that the acquired image is not the target to be calculated, analyzing the reason why the acquired image is not the target to be calculated based on the distance between each pair of feature points; When it is determined that the target to be monitored is in a moving state, contour features of the target to be monitored in the image are acquired, and the direction of the target to be monitored is determined based on the contour features.

5. The scalable infrared camera monitoring system based on stereo ranging according to claim 4 is characterized in that: The analysis module is further used to adjust the preset standard interval range based on the determined angle between the orientation of the target to be monitored and the direction facing the camera, wherein the expansion amount of the preset standard interval range is negatively correlated with the angle.

6. The scalable infrared camera monitoring system based on stereo ranging according to claim 2 is characterized in that: The analysis module is further used to calculate the average value of the distances between the feature point pairs to obtain a distance mean, and analyze the reasons why the acquired image is not a target to be calculated based on the distance mean, including: The reason for determining that the acquired image is not the target to be calculated is the environmental influence; The analysis module determines the reason why the acquired image is not the target to be calculated based on the mean value of each distance in the historical data, and makes a secondary determination. Or, the reason for determining that the acquired image is not the target to be calculated is that the acquisition is unqualified.

7. The scalable infrared camera monitoring system based on stereo ranging according to claim 6 is characterized in that: The analysis module is also used to correct the noise reduction factor based on the ambient brightness under the condition of environmental influence, wherein the increase in the noise reduction factor is positively correlated with the ambient brightness.

8. The scalable infrared camera monitoring system based on stereo ranging according to claim 6 is characterized in that: The analysis module is also used to calculate the distance variance of each distance mean in the historical data, and based on the distance variance, secondarily determine the reason why the acquired image is not the target to be calculated, including: The reason for determining that the acquired image is not the target to be calculated is the environmental influence. Or, the reason why the acquired image is determined to be a non-target to be calculated is that the detection distance does not match the camera position.

9. The scalable infrared camera monitoring system based on stereo ranging according to claim 8, characterized in that: The analysis module is further configured to adjust the distance between the first acquisition device and the second acquisition device based on the detection distance, wherein an increase in the distance is positively correlated with the detection distance.

10. The scalable infrared camera monitoring system based on stereo ranging according to claim 6, characterized in that: The analysis module is further configured to adjust the detection sensitivity based on the ambient temperature when the acquisition is determined to be unqualified, wherein the reduction in the detection sensitivity is negatively correlated with the ambient temperature.

Images