CN112037176A - Human presence detection device - Google Patents
Human presence detection device Download PDFInfo
- Publication number
- CN112037176A CN112037176A CN202010784617.2A CN202010784617A CN112037176A CN 112037176 A CN112037176 A CN 112037176A CN 202010784617 A CN202010784617 A CN 202010784617A CN 112037176 A CN112037176 A CN 112037176A
- Authority
- CN
- China
- Prior art keywords
- heat source
- value
- pixel point
- target
- image frame
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 241000282414 Homo sapiens Species 0.000 title claims abstract description 90
- 238000001514 detection method Methods 0.000 title claims abstract description 41
- 238000001931 thermography Methods 0.000 claims abstract description 58
- 238000000034 method Methods 0.000 claims description 13
- 238000004590 computer program Methods 0.000 claims description 3
- 238000003331 infrared imaging Methods 0.000 description 11
- 230000002159 abnormal effect Effects 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 238000004378 air conditioning Methods 0.000 description 3
- 230000007613 environmental effect Effects 0.000 description 3
- 208000015181 infectious disease Diseases 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 238000007670 refining Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 241001465754 Metazoa Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/0022—Radiation pyrometry, e.g. infrared or optical thermometry for sensing the radiation of moving bodies
- G01J5/0025—Living bodies
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
- G08B21/0407—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons based on behaviour analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J2005/0077—Imaging
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10048—Infrared image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30196—Human being; Person
Landscapes
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- Emergency Management (AREA)
- General Health & Medical Sciences (AREA)
- Gerontology & Geriatric Medicine (AREA)
- Social Psychology (AREA)
- Psychology (AREA)
- Psychiatry (AREA)
- Quality & Reliability (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Theoretical Computer Science (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Image Analysis (AREA)
Abstract
The embodiment of the invention discloses a human body existence detection device, which comprises a memory and a processor, wherein the processor calls a program stored in the memory and executes the following steps: acquiring a thermal imaging video, wherein the thermal imaging video comprises continuous image frames with preset frame numbers, the last frame of the thermal imaging video is a current image frame, and the pixel value of each pixel point in the image frame is a temperature value; according to the thermal imaging video and a preset sigma criterion, performing heat source pixel point detection on the current image frame to obtain a target image frame, wherein the target image frame comprises the detected heat source pixel points; and determining whether a human body exists in the current image frame according to the heat source pixel points contained in the target image frame. According to the technical scheme, self-adaptive denoising of the gradually-changed heat source in the environment can be effectively achieved, the change of the environment can be effectively adapted, the accuracy of heat source pixel point detection is improved, and the accuracy of human body existence detection is further improved.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a human body existence detection device.
Background
With the rapid development of social economy and the increasing enhancement of comprehensive national power, the living standard of people is gradually improved, the safety requirement for living is increased day by day, and the monitoring of living environment is an important part of living safety.
The infrared thermal imaging device can sense the temperature of an object in a monitored environment range, and is also applied to detecting whether a human body exists in safety monitoring. However, in a living environment, there are some interfering heat sources, for example, gradual heat sources caused by gradual environmental changes such as sunlight irradiation and air conditioning temperature adjustment, and the gradual heat sources existing in these environments affect the accuracy of detecting whether a human body is present or not by using an infrared thermal imaging apparatus.
Disclosure of Invention
The invention mainly aims to provide a human body existence detection device which can improve the accuracy of human body existence detection.
To achieve the above object, the present invention provides a human presence detection apparatus, comprising a memory and a processor, the memory storing a computer program, the computer program, when executed by the processor, causing the processor to perform the steps of:
acquiring a thermal imaging video, wherein the thermal imaging video comprises continuous image frames with preset frame numbers, the last frame of the thermal imaging video is a current image frame, and the pixel value of each pixel point in the image frame is a temperature value;
according to the thermal imaging video and a preset sigma criterion, performing heat source pixel point detection on the current image frame to obtain a target image frame, wherein the target image frame comprises the detected heat source pixel points;
and determining whether a human body exists in the current image frame according to the heat source pixel points contained in the target image frame.
The embodiment of the invention has the following beneficial effects:
the method comprises the steps of obtaining a thermal imaging video, wherein the thermal imaging video comprises continuous image frames with preset frame numbers, the last frame of the thermal imaging video is a current image frame, the pixel value of each pixel point in the image frames contained in the thermal imaging video is a temperature value, performing heat source pixel point detection on the current image frame according to the thermal imaging video and a preset sigma criterion to obtain a target image frame comprising the detected heat source pixel points, and determining whether a human body exists in the current image frame according to the heat source pixel points contained in the target image frame. By using the thermal imaging video and the preset sigma criterion, the heat source pixel point detection is carried out on the current image frame, the self-adaptive denoising of the gradual change heat source (such as solar irradiation, air conditioning and the like) in the environment can be effectively realized, the change of the environment can be effectively adapted, the heat source pixel point detection accuracy is improved, and the human body existence detection accuracy is further improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Wherein:
FIG. 1 is a schematic diagram of a hardware configuration of a human presence detection apparatus according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating method steps of a human presence detection method performed by a processor in an embodiment of the invention;
FIG. 3 is another flow chart illustrating method steps of a human presence detection method performed by a processor in accordance with an embodiment of the present invention;
FIG. 4 is a flow chart illustrating a refinement step of step 303 in the embodiment of FIG. 3;
FIG. 5 is a flow chart illustrating the step of refining step 304 in the embodiment of FIG. 3;
FIG. 6 is a flow chart illustrating additional steps of the embodiment shown in FIGS. 2 and 3.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a hardware structure diagram of a human presence detecting device according to an embodiment of the present invention, wherein the human presence detecting device 100 may be any type of electronic device with computing capability, for example: smart phones, computers, palmtop computers, tablet computers, and the like. In a specific example, the human presence detecting device may be an infrared thermal imaging device, or the human presence detecting device may also be a server, a cloud platform, or the like, which has a connection relationship with the infrared thermal imaging device, where the connection relationship may be a wired connection or a wireless connection.
Specifically, as shown in fig. 1, the human presence detection apparatus 100 includes one or more processors 102 and a memory 104. One processor 102 is illustrated in fig. 1. The processor 102 and the memory 104 may be connected by a bus or other means, such as by a bus in FIG. 1.
The memory 104, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as programs, instructions, and modules corresponding to the human presence detection method. The processor 102 executes various functional applications and data processing of the electronic device, i.e., implements the human presence detection method, by running non-volatile software programs, instructions, and modules stored in the memory 104.
The memory 104 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the human presence detecting device, and the like. Further, the memory 104 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 104 may optionally include memory located remotely from the processor 102, which may be connected to the human presence detection apparatus via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
In an embodiment of the present invention, the memory 104 is used for storing a computer-implemented program of the human presence detection method, and the processor 102 is used for reading and executing computer-readable instructions. In particular, the processor 102 may be configured to invoke a computer implemented program of the human presence detection method stored in the memory 104 and execute instructions contained in the computer implemented program to perform method steps related to the human presence detection method. With respect to the method steps of the human presence detection method performed by the processor 104, reference may be made to the following description of fig. 2-5.
Referring to fig. 2, a flowchart illustrating method steps of a human presence detection method executed by a processor according to an embodiment of the present invention is shown, where the method includes:
in the embodiment of the invention, the human body existence detection method is realized by the human body existence detection device.
In the embodiment of the invention, a thermal imaging video is obtained, and the thermal imaging video is obtained by shooting with a thermal infrared imaging device, wherein the thermal infrared imaging device applies an infrared thermal imaging technology, the infrared thermal imaging technology can detect an infrared specific waveband signal of object thermal radiation based on a photoelectric technology, the signal can be converted into an image which can be distinguished by human vision, and a temperature value is further calculated, so that the thermal imaging video comprises continuous image frames, and the pixel value of each pixel point in the image frames is the temperature value. It can be understood that by using infrared thermal imaging technology, human beings are beyond visual obstruction and can see the temperature distribution of the surface of the object.
When the human presence detection method in the embodiment of the present invention is executed, a thermal imaging video including image frames of consecutive preset frames may be used, and a last frame of the thermal imaging video is a current frame. The thermal imaging video may be captured by a thermal infrared imaging device, and the thermal infrared imaging device may capture the thermal imaging video at a preset frame rate and resolution, for example, at a frame rate of 16, that is, at a frequency of 16Hz, so that 16 image frames per second may be generated. The adopted resolution is 32 × 24, so that each frame of image comprises 32 × 24 pixels, and the pixel value of each pixel is a temperature value. It is understood that, in order to make the range of the photographed image as large as possible, the thermal infrared imaging device may be installed right above the space to be photographed, for example, if the thermal infrared imaging device is installed in a toilet, it may be installed at the center right above the roof of the toilet such that the photographing angle of the thermal infrared imaging device is vertically downward, and preferably, the installation height of the thermal infrared imaging device is 2.5m to 3.3 m.
It can be understood that, in the embodiment of the present invention, whether a human body exists may be detected in real time, or whether a human body exists is detected in a historical video, for better understanding, a video frame that needs to detect whether a human body exists is referred to as a current image frame, and the current image frame is a last frame of the acquired thermal imaging video. In addition, the preset number of frames included in the thermal imaging video may be determined based on specific needs, and may be set to 300000 frames, for example.
It should be noted that the thermal imaging video referred to in the embodiment of the present invention is a video captured by the thermal infrared imaging device under the condition that the capturing angle is fixed.
in the normal distribution, sigma (sigma) represents a standard deviation, μ represents a mean value, and in the standard two-dimensional coordinate system, u is a symmetric axis of the normal distribution pattern, the above-mentioned sigma (sigma) criterion is used to represent a probability of the numerical distribution, and may be any one of 1sigma criterion to 6sigma criterion, and in the case of 3sigma criterion, it represents that a probability of the numerical distribution in (μ -3 σ, μ +3 σ) is 0.9974, and it can be considered that almost all y values corresponding to x in the standard coordinate system are concentrated in the (μ -3 σ, μ +3 σ) interval.
In the embodiment of the present invention, because the thermal imaging video is a video captured by the thermal infrared imaging device under the condition of a fixed capture angle, pixel values of pixel points included in each image frame in the thermal imaging video conform to normal distribution, and the pixel values of the pixel points included in each image frame in the thermal imaging video satisfy the 3sigma criterion, and are not affected by environmental gradual change, so as to adapt to environmental changes. Therefore, the heat source pixel point detection can be carried out on the current image frame based on the thermal imaging video and the 3sigma criterion to obtain a target image frame, wherein the target image frame comprises the detected heat source pixel points. The heat source pixel points refer to pixel points corresponding to a heat source in an image frame, the pixel values of the heat source pixel points are usually regarded as abnormal values, and the heat source pixel points are pixel points which do not accord with the 3sigma criterion.
And step 203, determining whether a human body exists in the current image frame according to the heat source pixel points contained in the target image frame.
In the embodiment of the invention, the thermal source pixel point detection is carried out on the current image frame by using the thermal imaging video and the preset sigma criterion, so that the self-adaptive denoising of gradual change heat sources (such as solar irradiation, air conditioning and the like) in the environment can be effectively realized, the change of the environment can be effectively adapted, the accuracy of the heat source pixel point detection is improved, and the accuracy of human body existence detection is further improved.
For better understanding of the technical solution in the embodiment of the present invention, please refer to fig. 3, fig. 3 is another schematic flow chart of the method steps of the human presence detecting method executed by the processor in the embodiment of the present invention, including:
301, acquiring a thermal imaging video, wherein the thermal imaging video comprises continuous image frames with preset frame numbers, the last frame of the thermal imaging video is a current image frame, and the pixel value of each pixel point in the image frame is a temperature value;
in the embodiment of the present invention, the content related to step 301 is similar to the content related to step 201 in the embodiment shown in fig. 2, and specific reference may be made to the description related to step 201 in the embodiment shown in fig. 2, which is not described herein again.
Further, the thermal imaging video may be a history data list with a preset length, one image frame acquired by the thermal infrared imaging device is added to the history data list each time, and since the length of the history data list is limited, the oldest image frame in the history data list is deleted each time one image frame is added after the history data list is full.
in the embodiment of the present invention, for a target pixel point in a current image frame, a mean value and a standard deviation of pixel values of pixel points in each image frame included in the thermal imaging video and having the same position as the target pixel point may be calculated and used as the mean value and the standard deviation of the pixel values of the target pixel point, where the target pixel point is any one pixel point in the current image frame.
For better understanding, taking the image resolution of the thermal imaging video as 24 × 32 as an example, each image frame in the thermal imaging video includes 768 pixels, and the thermal imaging video may be first subjected to array transformation, that is, Ln×768N represents the number of image frames in the thermal imaging video, and in the array, one image frame represents one line, and within one lineThe plane contains columns of 768 pixels of the image frame. Meanwhile, the current frame image can be subjected to digital conversion, namely A768It means that the array has only one row, and the row includes 768 columns, and each column corresponds to the pixel value of one pixel point in the current frame image.
Take the target pixel point as the ith pixel point in the current frame image as an example, for AiCan be given to Ln×768Carrying out mean solution on the ith row to obtain a mean value AiPixel value mean of (A)iCan utilize Ln×768The standard deviation value is solved in the ith column, and the obtained standard deviation value is AiThe range of i is 1 to 768, and according to the method, the mean value of the pixel values and the standard deviation value of each pixel point in the current frame image can be obtained.
Further, based on sigma criterion, the pixel value of the target pixel point in the target image frame is obtained according to the pixel value mean value and the standard difference value of the target pixel point and the pixel value of the target pixel point in the current image frame, and whether the target pixel point is a heat source pixel point is determined based on the pixel value of the target pixel point.
Specifically, please refer to fig. 4, which is a schematic flow chart illustrating a detailed step of step 303 in the embodiment of fig. 3 of the present invention, including:
For step 401, in a feasible implementation manner, a 3sigma criterion may be used to calculate a residual pixel value of a target pixel, where the residual pixel value is obtained by subtracting a mean value of pixel values of the target pixel in a current frame and then subtracting a standard deviation value of the target pixel by 3 times, and a residual value is used as the residual pixel value of the target pixel, and is specifically represented as follows:
bi＝Ai-mean(Li×768,axis＝0)-3×std(Li×768,axis＝0)
wherein, biRepresenting the residual pixel value, A, of the ith target pixel pointiThe pixel value, mean (L) of the ith target pixel point in the current frame image is representedi×768Where "axis" is 0) represents the pixel value mean of the ith target pixel point, std (L)i×768And axis is 0) represents the standard deviation value of the ith target pixel point.
By the method, the residual pixel value of the target pixel point can be obtained, further, the pixel value of the target pixel point in the target image frame can be determined according to the residual pixel value, and whether the target pixel point is a heat source pixel point is determined based on the pixel value of the target pixel point.
Specifically, when the residual pixel value is larger than a preset threshold value, determining that the pixel value of a target pixel point in a target image frame is a first numerical value, and the target pixel point is a heat source pixel point; and when the residual pixel value is less than or equal to the preset threshold value, determining that the pixel value of the target pixel point in the target image frame is a second numerical value, and the target pixel point is a non-heat source pixel point. The first numerical value may be 1, the second numerical value may be 0, that is, binarization processing may be performed based on the remaining pixel value, where the preset threshold value may be 0, that is, when the remaining pixel value is greater than 0, it is determined that a pixel value of the target pixel point in the target image frame is 1 and is a heat source pixel point, and when the remaining pixel value is less than or equal to 0, it is determined that a pixel value of the target pixel point in the target image frame is 0 and is a non-heat source pixel point. It can be understood that when the 3sigma criterion is used and the remaining pixel value of the target pixel point is greater than 0, it indicates that the target pixel point does not conform to the 3sigma criterion and belongs to an abnormal pixel point, in the embodiment of the present invention, the pixel point corresponding to the heat source is generally regarded as an abnormal pixel point having a different pixel value characteristic from that of the surrounding environment or the object, and therefore, the abnormal pixel point can be effectively identified by using the 3sigma criterion, that is, the heat source pixel point is obtained.
For the sake of understanding, based on the example that the image resolution of the thermal imaging video in step 303 is 24 × 32, the array B composed of the remaining pixels of the current frame image can be obtained768The array B768The expression of (a) is as follows:
B768＝A768-mean(Ln×768,axis＝0)-3×std(Ln×768,axis＝0)
wherein mean (A)n×768Axis ═ 0) represents an array Ln×768Is a 768-dimensional array, std (L)n×768Axis ═ 0) represents an array Ln×768Is a 768-dimensional array.
Then to array B768The residual pixel value of each row in the array is judged, when the residual pixel value is more than 0, the value is charged to be 1, when the residual pixel value is less than 0, the value is reset to be 0, and then a new array C is obtained768And performing dimension transformation on the array, and converting the array into a 24 × 32 format to obtain the target image frame.
And step 304, determining whether a human body exists in the current image frame according to the heat source pixel points contained in the target image frame.
In the embodiment of the invention, after the target image frame containing the heat source pixel points is obtained, whether a human body exists in the current image frame or not is determined.
Referring to fig. 5, a flow chart of a step of refining step 304 in the embodiment of the present invention is shown, where step 204 specifically includes:
502, determining a heat source density value of each heat source pixel point according to the position coordinate value of each heat source pixel point, wherein the heat source density value represents the number of the heat source pixel points in a preset range with the heat source pixel points as centers;
In an embodiment of the present invention, the position coordinate value of each heat source pixel in the target image frame may be determined first, and the position coordinate value may be determined based on the row and the column of the heat source pixel in the target image frame, for example, if the resolution of the target image frame is 24 × 32, it indicates that the target image frame includes 24 rows and 32 columns, and the position coordinate value of the heat source pixel may be determined to be (a1, a2), a1 represents the row where the heat source pixel is located, and a2 represents the column where the heat source pixel is located.
Further, determining the heat source density value of each heat source pixel point according to the position coordinate value of each heat source pixel point, wherein the heat source density value represents the number of the heat source pixel points in a preset range with the heat source pixel points as the centers, and determining whether a human body exists in the current frame image according to the heat source density value of each heat source pixel point. The heat source density value can be used to distinguish the type of the heat source in the target frame image, such as whether a small infection heat source is included (a small interference heat source generally refers to a heat source of a small object such as a water heater, a small animal, etc.), whether a human body is included, and the like.
In a feasible implementation manner, the manner of obtaining the heat source density value of the heat source pixel point may be as follows:
d1, calculating the distance between the target heat source pixel point and other heat source pixel points except the target heat source pixel point in the target image frame to obtain a distance set of the target heat source pixel point, wherein the target heat source pixel point is any one heat source pixel point in the target image frame;
and d2, determining the distance number of the distance values smaller than or equal to the preset distance threshold in the distance set, and determining the distance number as the heat source density value of the target heat source pixel point.
In order to better understand the technical solution in the embodiment of the present invention, a target image frame includes 20 heat source pixels, the number of the 20 heat source pixels is 1 to 20, for each heat source pixel, a heat source density value is determined, for the heat source pixel 1, the distances between the heat source pixel 1 and the heat source pixels 2 to 20 are calculated to obtain a distance set 1 of the heat source pixel 1, the distance set includes e2, e3, … …, and e20, e2 represents the distance value from the heat source pixel 1 to the heat source pixel 2, e20 represents the distance value from the heat source pixel 1 to the heat source pixel 20, and so on, further, the number of distances between the distance set 1 of the heat source pixel 1 and the distance value smaller than or equal to a preset distance threshold is determined, the preset distance threshold is used for determining the range centered on the heat source pixel 1, if the number of distances less than or equal to the preset distance threshold is M, the heat source density value of the heat source pixel point 1 is determined to be M, and the calculation methods of the heat source density values of other heat source pixel points are also the same, which is not described herein again.
In the embodiment of the invention, the heat source density value of the heat source pixel point is used for distinguishing the human body from the small interference heat source, under the normal condition, the heat source density value of the human body is larger, and the density value of the small infection heat source is smaller.
Specifically, the target number of the heat source pixel points in the target image frame, in which the heat source density value is greater than or equal to the preset density threshold, may be determined. And when the number of the target images is larger than or equal to a preset value, determining that a human body exists in the current frame image, and when the number of the target images is smaller than the preset value, determining that the human body does not exist in the current frame image. It can be understood that, since the heat source secret value is a pixel point for distinguishing whether the heat source pixel point is a human body heat source, if the heat source density value of one heat source pixel point is greater than the preset density threshold, it indicates that a human body exists, that is, the preset value is preferably 1.
In the embodiment of the invention, the small-sized infection heat source can be effectively filtered by calculating the heat source density value of the heat source pixel point and comparing the heat source density value with the preset density threshold value, so that the interference of the small-sized interference heat source on the detection of whether a human body exists is reduced, and the misjudgment rate is reduced.
Optionally, under the condition that the human body exists in the current frame image, whether the time for the human body to exist is too long or not can be further determined, if the time is too long, an alarm needs to be given, and the scheme is preferably applied to a home scene, an old home scene and the like so as to give an alarm in time when the weak groups such as the old, the children and the like possibly have abnormal conditions.
Please refer to fig. 6, which is a flowchart illustrating additional steps of the embodiments shown in fig. 2 and fig. 3 according to the present invention, including:
and 603, outputting a human body overtime stay alarm when the time difference is greater than or equal to a preset time threshold.
A time stamp list may be preset, the time stamp list having an initial state of being empty and to which an image frame determined that a human body exists is added each time the presence of the human body is detected, wherein the time stamp list is used to store time stamps of consecutive multi-frame image frames, and each frame image frame detects the presence of the human body. For example, if N frames of image frames have been stored in the timestamp list, it indicates that a human body is detected in all the N frames of image frames, and the N frames of image frames are consecutive image frames, when it is determined that a human body exists in a next frame of the N frames of image frames, that is, in the case that N +1 frames of image frames according to the technical solution in the embodiment of the present invention, the N +1 frames of image frames are also stored in the timestamp list, and if it is determined that a human body does not exist, the timestamp list is cleared. By setting the timestamp list, the time length for detecting the existence of the human body can be determined, and whether the human body overtime stay alarm needs to be performed or not can be further determined.
Specifically, in the embodiment of the present invention, when it is determined that a human body exists in the current image frame, the timestamp of the current image frame is added to the timestamp list, and a time difference between a first timestamp and a last timestamp in the timestamp list is determined, when the time difference is greater than or equal to a preset time threshold, it indicates that the human body staying time has reached the warning standard, and a human body timeout staying alarm is output in various output manners, for example, a short message is sent to a specified telephone number, a call is made, and the like, or an alarm is controlled to send an alarm sound. In practical application, the output mode of the human body overtime staying alarm can be set according to specific needs, which is not limited herein.
Above-mentioned, human existence detection device carries out heat source pixel point to current image frame through using thermal imaging video and preset sigma criterion to detect for can get rid of the influence of the gradual change heat source in the environment based on sigma criterion, effectively realize the heat source pixel point like human heat source and small-size interference heat source etc. the accuracy of heat source pixel point of discernment is high, can help improving the accuracy that human existence detected. Furthermore, the human body heat source and the small interference heat source can be effectively distinguished by utilizing the heat source density value of the heat source pixel points, and the accuracy of human body existence detection is further improved. In addition, the time length for detecting the existence of the human body can be determined in a mode of setting a time stamp list, so that whether the human body stay overtime alarm needs to be carried out or not is determined based on the time length, the method and the device are particularly suitable for home scenes and old people home scenes, and the safety of the human body can be ensured.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (8)
1. A human presence detection apparatus comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of:
acquiring a thermal imaging video, wherein the thermal imaging video comprises continuous image frames with preset frame numbers, the last frame of the thermal imaging video is a current image frame, and the pixel value of each pixel point in the image frame is a temperature value;
according to the thermal imaging video and a preset sigma criterion, performing heat source pixel point detection on the current image frame to obtain a target image frame, wherein the target image frame comprises the detected heat source pixel points;
and determining whether a human body exists in the current image frame according to the heat source pixel points contained in the target image frame.
2. The apparatus of claim 1, wherein the processor performs the following steps in performing the step of performing heat source pixel point detection on the current image frame according to the thermal imaging video and a preset sigma criterion to obtain a target image frame:
calculating a target pixel point in the current image frame, wherein the mean value and the standard difference value of pixel values of pixel points at the same position in each image frame contained in the thermal imaging video are used as the mean value and the standard difference value of the pixel values of the target pixel point, and the target pixel point is any one pixel point in the current image frame;
based on the sigma criterion, obtaining the pixel value of the target pixel point in the target image frame according to the pixel value mean value and the standard difference value of the target pixel point and the pixel value of the target pixel point in the current image frame, and determining whether the target pixel point is the heat source pixel point based on the pixel value of the target pixel point.
3. The apparatus of claim 2, wherein the processor performs the following steps in the process of obtaining the pixel value of the target pixel point in the target image frame according to the mean value and the standard deviation value of the pixel value of the target pixel point and the pixel value of the target pixel point in the current image frame based on the sigma criterion, and determining whether the target pixel point is the heat source pixel point based on the pixel value of the target pixel point:
subtracting the pixel value mean value of the target pixel point from the pixel value of the target pixel point in the current image frame, and subtracting the standard difference value of the target pixel point by a preset multiple to obtain the residual pixel value of the target pixel point;
and determining the pixel value of the target pixel point in the target image frame according to the residual pixel value, and determining whether the target pixel point is a heat source pixel point based on the pixel value of the target pixel point.
4. The apparatus of claim 3, wherein the processor performs the following steps in the course of determining the pixel value of the target pixel in the target image frame according to the residual pixel value and determining whether the target pixel is a heat source pixel based on the pixel value of the target pixel:
when the residual pixel value is larger than a preset threshold value, determining that the pixel value of the target pixel point in the target image frame is a first numerical value, and the target pixel point is the heat source pixel point;
when the residual pixel value is smaller than or equal to the preset threshold value, determining that the pixel value of the target pixel point in the target image frame is a second numerical value, and the target pixel point is a non-heat source pixel point.
5. The apparatus according to any one of claims 1 to 4, wherein the processor, during the step of determining whether a human body exists in the current image frame according to the heat source pixel points included in the target image frame, specifically performs the following steps:
determining position coordinate values of all heat source pixel points in the target image frame;
determining a heat source density value of each heat source pixel point according to the position coordinate value of each heat source pixel point, wherein the heat source density value represents the number of the heat source pixel points in a preset range with the heat source pixel points as centers;
and determining whether a human body exists in the current frame image according to the heat source density value of each heat source pixel point.
6. The apparatus of claim 5, wherein the processor, during the step of determining the heat source density value of each heat source pixel point according to the position coordinate value of each heat source pixel point, specifically performs the following steps:
calculating the distance between a target heat source pixel point and other heat source pixel points except the target heat source pixel point in the target image frame to obtain a distance set of the target heat source pixel point, wherein the target heat source pixel point is any one heat source pixel point in the target image frame;
determining the number of distances of distance values smaller than or equal to a preset distance threshold in the distance set, and determining the number of distances as the heat source density value of the target heat source pixel point.
7. The apparatus of claim 5, wherein the processor, during the step of determining whether the human body exists in the current frame image according to the heat source density values of the heat source pixel points, specifically performs the following steps:
determining the target number of heat source pixel points with the heat source density value larger than or equal to a preset density threshold value in the target image frame;
when the number of the targets is larger than or equal to a preset value, determining that a human body exists in the current frame image frame;
and when the target number is smaller than the preset value, determining that no human body exists in the current frame image.
8. The apparatus according to any one of claims 1 to 4, wherein the processor, after performing the step of determining whether a human body exists in the current image frame according to the heat source pixel points contained in the target image frame, is further configured to perform the following steps:
if the human body exists in the current image frame, adding a timestamp of the current image frame into a timestamp list, wherein the timestamp list comprises timestamps of continuous multi-frame image frames, and each frame of image frame detects the existence of the human body;
determining a time difference between a first timestamp and a last timestamp in the list of timestamps;
and outputting a human body overtime stay alarm when the time difference is greater than or equal to a preset time threshold.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010784617.2A CN112037176A (en) | 2020-08-06 | 2020-08-06 | Human presence detection device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010784617.2A CN112037176A (en) | 2020-08-06 | 2020-08-06 | Human presence detection device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112037176A true CN112037176A (en) | 2020-12-04 |
Family
ID=73582700
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010784617.2A Pending CN112037176A (en) | 2020-08-06 | 2020-08-06 | Human presence detection device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112037176A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112924035A (en) * | 2021-01-27 | 2021-06-08 | 复旦大学附属中山医院 | Body temperature and respiration rate extraction method based on thermal imaging sensor and application thereof |
-
2020
- 2020-08-06 CN CN202010784617.2A patent/CN112037176A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112924035A (en) * | 2021-01-27 | 2021-06-08 | 复旦大学附属中山医院 | Body temperature and respiration rate extraction method based on thermal imaging sensor and application thereof |
| CN112924035B (en) * | 2021-01-27 | 2022-06-21 | 复旦大学附属中山医院 | Body temperature and respiration rate extraction method based on thermal imaging sensor and application thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111489342B (en) | Video-based flame detection method, system and readable storage medium | |
| CN111462155B (en) | Motion detection method, device, computer equipment and storage medium | |
| WO2022041484A1 (en) | Human body fall detection method, apparatus and device, and storage medium | |
| CN111426393A (en) | Temperature correction method, device and system | |
| CN107122743B (en) | Security monitoring method and device and electronic equipment | |
| CN103714319A (en) | Video intrusion detection method used for power line external force damage-prevention system | |
| US8934020B2 (en) | Integrated video quantization | |
| CN113628404A (en) | Method and device for reducing invalid alarm | |
| CN112562159B (en) | Access control method and device, computer equipment and storage medium | |
| CN114863357A (en) | Method and system for identifying and alarming external force damage of power transmission line | |
| CN105469054A (en) | Model construction method of normal behaviors and detection method of abnormal behaviors | |
| CN112037176A (en) | Human presence detection device | |
| CN114758300A (en) | Method, device and equipment for judging malicious shielding of scene and readable storage medium | |
| CN111240223A (en) | Intelligent household control method and related product | |
| CN112101104B (en) | Human body presence detection method and related device | |
| US9607210B2 (en) | Video surveillance system and method for fraud detection | |
| US11393091B2 (en) | Video image processing and motion detection | |
| CN111445411B (en) | Image denoising method, image denoising device, computer equipment and storage medium | |
| CN114553725B (en) | Machine room monitoring alarm method and device, electronic equipment and storage medium | |
| CN114550256A (en) | Method, device and equipment for detecting tiny target and computer readable medium | |
| CN112102264A (en) | Human body detection device | |
| Sofwan et al. | Implementation of vehicle traffic analysis using background subtraction in the Internet of Things (IoT) architecture | |
| CN115482175A (en) | Multi-scale fusion method, device and equipment for infrared image and visible light image | |
| CN111225178A (en) | Video monitoring method and system based on object detection | |
| JP7492595B2 (en) | Monitoring system, analysis device, and AI model generation method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20201204 |