CN113313917B - Method for solving false alarm generated when no target exists in front of detector in sitting posture detection - Google Patents
Method for solving false alarm generated when no target exists in front of detector in sitting posture detection Download PDFInfo
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- G—PHYSICS
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- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
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- G08B21/18—Status alarms
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
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- G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
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- G—PHYSICS
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
Abstract
The invention provides a method for solving the problem of false alarm generated when no target exists in front of a detector in sitting posture detection, which comprises the following steps: s1, a sitting posture calculation module is processed for the first time; s2, registering a standard sitting posture; s3 determining whether registration was successful If not, performing S2; if yes, S4 is carried out; s4, processing the sitting posture calculation module again; s5, comparing the real-time sitting posture data with the standard sitting posture data; s6 determines whether the deviation exceeds a threshold If not, entering S4; if yes, S7 is carried out; s7 determines whether the state duration exceeds a specified period If not, entering S4, if yes, carrying out S8; s8, judging whether a target exists or not: judging by a face counting accumulator, if the face counting accumulator is not more than 1, detecting no face in the detection period, judging that no target person is in the detection range of the detector, and carrying out S9; s9, alarming for abnormal sitting posture; s10, processing the sitting posture calculation module again; s11, comparing the real-time sitting posture data with the standard sitting posture data again; s12, determine whether the sitting posture meets the standard If not, entering S9; if yes, the alarm is cancelled, and S4 is entered.
Description
Technical Field
The invention relates to the field of face recognition, in particular to a method for solving false alarm generated when no target exists in front of a detector in sitting posture detection.
Background
With the continuous development of science and technology, particularly the development of computer vision technology, the face recognition technology is widely applied to various fields such as information security, electronic authentication and the like, and the image feature extraction method has good recognition performance. Among them, sitting posture detection is also an important content in the field of recognition. In the prior art, the method comprises the steps of 1, measuring the distance between a person and a sensor based on ultrasonic waves, laser lines and the like, and judging whether the sitting posture is standard or not according to the distance. 2. Based on a common image sensor, feature data such as a face angle, a human figure posture and the like are obtained and are matched with preset standard posture feature data so as to judge whether the sitting posture is abnormal or not.
However, in the prior art, there are the following drawbacks:
1. the method has the advantages that the distance between a person and a detection device is detected based on laser rays and ultrasonic waves, whether the sitting posture of the person is correct or not is judged according to the detection result, the method can achieve the effect of detecting large-amplitude posture changes, but the method cannot accurately judge local unhealthy sitting postures such as a side face and a head bending position, and the ultrasonic waves and the laser rays used by the methods are harmful to the health of the person in the radioactive environments for a long time.
2. The patent CN102096801A is based on information of an image, by obtaining an inclination angle of a face, an area difference of a glasses area, a head-shoulder curve difference, and making a difference with initially obtained standard data exceeding a preset threshold, namely, a sitting posture abnormality, because in the method, only the difference between normal and abnormal sitting postures of the object to be detected in the detection range is solved, and the condition that the object to be detected leaves the detection range is not solved, at this time, the detector can be caused to judge abnormality to trigger an abnormal sitting posture alarm, which affects the use experience.
3. Patent CN110334631A is based on face detection and sitting posture detection of binary operation, uses adaboost face detection algorithm to position the head position of a standard sitting posture, sets tolerance as a standard, and detects whether the target head position exceeds the standard tolerance as a sitting posture abnormality judgment standard. Because of being based on shallow face detection algorithm or deep CNN face detection algorithm such as the adboost, there is certain limit to face detection ability, and too big or the application environment complicacy of face angle can lead to face detection algorithm unable to detect the people face, influences follow-up judgement, and this kind of condition can lead to reporting by mistake and produce with the unable differentiation of unmanned face detection output condition when the target of waiting to detect normally leaves the detection range.
Common terms in the prior art include:
1. the face detection module: an image containing a complete face is input, and the face detection module returns the bounding box (bounding box) coordinates of the face in the image.
2. Face space angle: consists of three angles of pitch, yaw and roll of a human face, wherein pitch is a rotation around the y-axis; yaw is rotation about the z-axis; the roll is rotated about the x-axis. The explanation for pitch, yaw, roll is shown in FIG. 3.
3. Face angle detection module: inputting a gray image of ROI data of a human face, and acquiring a spatial angle of the human face, wherein the ROI (region of interest) is an interested area. In machine vision and image processing, a region to be processed, called a region of interest, ROI, is delineated from a processed image in the form of a box, circle, ellipse, irregular polygon, or the like.
4. Face count accumulator: and when the face detection module detects a face, the face counting accumulator performs an addition 1 operation.
5. Undetected face count accumulator: and when the face detection module does not detect the face, the undetected face counting accumulator is added with 1 for operation.
6. Sitting posture information: the system comprises a face space angle, face space position information, a face counting accumulator and an undetected face counting accumulator.
7. Standard sitting posture information: a person has one or more sets of sitting posture information collected by the present invention while sitting at a table or other location in a standard posture.
8. IOU: the IOU is called Intersection over Union, and calculates the ratio of the Intersection and Union of two bounding boxes, as shown in fig. 4, and IOU = Intersection/Union. IOU: one concept used in target detection is the overlap ratio of the generated candidate frame (candidate frame) and the original labeled frame (ground truth frame), i.e. the ratio of their intersection to union.
9. Face spatial position offset value: and calculating the IOU of the bounding box as the face position deviation value according to the bounding box detected in the step 1.
Disclosure of Invention
In order to solve the above problems, the present invention is directed to: a new method is provided for solving the problem that when a common image sensor is used, the extraction result of the human face and human shape posture characteristics under the condition that no target character exists and the result of the human face and human shape characteristics which cannot be normally extracted under the condition that the target character exists cannot be distinguished in a sitting posture detection scheme based on a human face and human shape posture characteristic extraction algorithm.
Specifically, the invention provides a method for solving the problem of false alarm generated when no target exists in front of a detector in sitting posture detection, which comprises the following steps:
s1, handle position of sitting calculation module for the first time for acquire position of sitting information, include: the system comprises a face detection module, a face angle detection module, a sitting posture information calculation module, a face counting accumulator and an undetected face counting accumulator;
s2, registering a standard sitting posture;
s3, determining whether the registration is successful? If not, re-entering the step S2; if yes, carrying out the next step;
s4, processing the sitting posture calculation module again to obtain sitting posture information;
s5, comparing the real-time sitting posture data with the standard sitting posture data;
s6, determine whether the deviation exceeds a threshold? If not, re-entering the step S4; if yes, carrying out the next step;
s7, determine whether the state duration exceeds a specified period? If not, re-entering the step S4, and if so, performing the next step;
s8, judging whether a target exists or not:
judging a face counting accumulator, if the face counting accumulator is not more than 1, determining that no face is detected in the detection period, and determining that no target person is in the detection range of the detector, and performing the next step S9;
s9, alarming for sitting posture abnormity, and assigning Alarm =1;
s10, processing the sitting posture calculation module again to obtain sitting posture information;
s11, comparing the real-time sitting posture data with the standard sitting posture data again;
s12, judging whether the sitting posture meets the standard? If not, re-entering the step S9; if yes, the Alarm is cancelled, alarm =0 is reset, and the step S4 is re-entered.
Thus, the present application has the advantages that: by adopting the method, the sitting posture can be detected only by using a common image sensor, the abnormal sitting posture alarm can be realized, the influence of similar ultrasonic waves and laser rays on the human health can be avoided, the product cost can be reduced, and particularly, the method well solves the problem that the extraction result of the human face and human-shaped posture characteristics under the condition without a target figure and the extraction result of the human face and human-shaped characteristics which are not normally extracted by the target figure cannot be distinguished in the prior art.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention.
Fig. 1 is a schematic block diagram of a flow chart of a method to which the present invention relates.
FIG. 2 is a schematic block diagram of a sitting posture calculation module in steps of the method of the present invention.
FIG. 3 is a schematic view of the sitting posture detection of the present invention.
Fig. 4 is a schematic diagram of the IOU ratio to which the present invention relates.
Detailed Description
In order that the technical contents and advantages of the present invention can be more clearly understood, the present invention will be further described in detail with reference to the accompanying drawings.
As shown in FIG. 1, the present invention relates to a method for solving the false alarm generated when there is no target in front of the detector in the sitting posture detection, which comprises the following steps:
s1, handle position of sitting calculation module for the first time for acquire position of sitting information, include: the sitting posture detecting device comprises a face detecting module, a face angle detecting module, a sitting posture information calculating module, a face counting accumulator and an undetected face counting accumulator;
s2, registering a standard sitting posture;
s3, determining whether the registration is successful? If not, re-entering the step S2; if yes, the next step is carried out;
s4, processing the sitting posture calculation module again to obtain sitting posture information;
s5, comparing the real-time sitting posture data with the standard sitting posture data;
s6, determining whether the deviation exceeds a threshold? If not, re-entering the step S4; if yes, the next step is carried out;
s7, determine whether the state duration exceeds a specified period? If not, re-entering the step S4, and if so, performing the next step;
s8, judging whether a target exists or not:
judging the face counting accumulator, if the face counting accumulator is not more than 1, judging that no face is detected in the detection period, judging that no target person is in the detection range of the detector, and performing the next step S9;
s9, alarming for sitting posture abnormity, and assigning Alarm =1;
s10, processing the sitting posture calculation module again to obtain sitting posture information;
s11, comparing the real-time sitting posture data with the standard sitting posture data again;
s12, judging whether the sitting posture meets the standard? If not, re-entering the step S9; if yes, the Alarm is cancelled, alarm =0 is reset, and step S4 is re-entered.
As shown in fig. 2, the processing sitting posture calculating module of step S1, S4 or S10 further includes:
a, the face detection module obtains a face bounding box from image data;
b, deducting human face ROI data according to the human face boundary frame and transmitting the human face ROI data to a human face angle detection module, acquiring a human face space angle, adding 1 to a human face counting accumulator, wherein when the human face detection module cannot acquire the human face boundary frame from image data, the human face counting accumulator does not process, and the human face counting accumulator is not detected and is added with 1;
and c, integrating the face bounding box to be obtained and the face space angle together by the sitting posture information calculating module, and updating the face counting accumulator and the undetected face counting accumulator for other modules to calculate.
Step S2, registering a standard sitting posture, further comprising: the sitting posture information is obtained through the step S1, the sitting posture information obtained from one frame of data is used as a result, and the sitting posture information results with the preset number n are continuously obtained, wherein n is a positive integer larger than or equal to 3.
In the step S2, the method further includes: the condition for judging the success of registering the standard sitting posture is that,
1) At least 3 maximum values of the angle deviation values in the sitting posture information result are smaller than a preset first threshold value;
2) The spatial position deviation value meets a preset second threshold value;
3) The above two conditions 1) and 2) must be satisfied simultaneously, then the standard sitting posture registration is successful.
Comparing the real-time sitting posture with the standard sitting posture deviation in the step S5 or S11 further comprises:
A. in the detection, acquiring sitting posture information of the current frame and performing deviation calculation on the registered sitting posture information;
B. and calculating a face space angle deviation value and a face space position deviation value.
In step S6, whether the deviation exceeds a threshold value further includes: if one or both of the calculated human face space angle deviation value and the human face space position deviation value exceed the preset threshold value, or the human face counting accumulator is not detected to exceed the preset threshold value, the current sitting posture is considered to be abnormal, and the next step S7 is carried out.
In step S7, determining whether the state duration exceeding the threshold exceeds a specified period further includes: when the deviation exceeds a threshold value, starting to accumulate the number of the sitting posture abnormal frames and starting to time when the sitting posture is judged to be abnormal, and when the sitting posture abnormal count exceeds a preset number in the specified period, confirming that the abnormal sitting posture is established, giving an alarm signal, and performing the next step S8; otherwise, the information is considered to be false information, the step S4 of the sitting posture calculation module is carried out again, and the sitting posture data information is continuously monitored.
The preset times are positive integers larger than 1.
Said gives an Alarm signal and Alarm =1.
In step S8, if it is determined that the target person is not within the detection range of the detector, the Alarm signal is cancelled, and Alarm =0.
The specified period is a preset time period, for example, 1 minute or 3 minutes, and is preset according to the needs of the customer.
The preset times are positive integers larger than 1, such as 1 time, 3 times or 5 times, 10 times and the like, and are set according to the needs of customers.
The methods for calculating the face spatial angle deviation value, the face spatial position deviation value, and the preset threshold are already well-established prior art, for example, refer to the schemes in patents CN102096801A and CN110334631A, etc., and will not be described herein again.
In addition, the technical solutions specifically referred to in the present application can be further explained as follows:
1. a sitting posture calculation module:
the face detection module obtains a face bounding box from the image data, deducts face ROI data according to the face bounding box and transmits the face ROI data to the face angle detection module, obtains a face space angle, adds 1 to a face counting accumulator, and when the face detection module cannot obtain the face bounding box from the image data, the face counting accumulator does not process, and the face counting accumulator is not detected and adds 1. And calculating sitting posture information, namely integrating the obtained face bounding box and the face space angle, and updating the face counting accumulator and the undetected face counting accumulator for other modules to calculate.
2. Registering a standard sitting posture:
the sitting posture information is acquired through the sitting posture detection module 1, the sitting posture information acquired by one frame of data is used as a result, and the preset number of sitting posture results are continuously acquired. The condition for successfully verifying the sitting posture registration comprises 1) that the maximum value of three angle deviations in the sitting posture result is smaller than a preset threshold value and 2) that the spatial position deviation value meets the preset threshold value. The two conditions are met simultaneously, namely the standard sitting posture registration is successful.
3. Comparing the deviation between the real-time sitting posture and the standard sitting posture:
and in the detection, the sitting posture information of the current frame and the registered sitting posture information are obtained to carry out deviation calculation, and a face space angle deviation value and a face space position deviation value are calculated.
4. Deviation exceeds a threshold:
if the two deviation values obtained by calculation in step 3 do not exceed the preset threshold value, the currently collected sitting posture is considered to be normal, and the sitting posture information is continuously monitored, and if one of the two deviation values exceeds the preset threshold value, or both of the two deviation values exceed the preset threshold value, or the undetected face counting accumulator exceeds the preset threshold value, the currently collected sitting posture is considered to be abnormal, and the next judgment is carried out.
5. The state duration period:
and when the sitting posture is judged to be abnormal in step 4, accumulating the number of the abnormal sitting posture frames and starting timing at the same time, when the abnormal sitting posture count exceeds a preset threshold value in a preset time period, confirming that the abnormal sitting posture is established, wherein Alarm =1, giving an Alarm signal, otherwise, considering the abnormal sitting posture count as false information, and continuing calculating by the sitting posture calculation module.
6. Judging whether a target exists or not:
and judging a face counting accumulator, if the face counting accumulator is not more than 1, determining that no face is detected in the detection period, determining that no target person is in the detection range of the detector, canceling the Alarm signal when Alarm =0, and starting to perform the steps 1, 3 and 4.
7. Whether the sitting posture is standard or not:
and when the Alarm signal of Alarm =1 is triggered in the step 5, starting to perform the steps 1, 3 and 4, and if the sitting posture is judged to be normal in the step 4, cancelling the Alarm signal of Alarm =1. And continuing the steps 1, 3 and 4 to monitor the sitting posture information.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the embodiment of the present invention by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for solving the problem of false alarm generated when no target exists in front of a detector in sitting posture detection is characterized by comprising the following steps:
s1, handle position of sitting calculation module for the first time for acquire position of sitting information, include: the sitting posture detecting device comprises a face detecting module, a face angle detecting module, a sitting posture information calculating module, a face counting accumulator and an undetected face counting accumulator; when the face detection module can not obtain the face bounding box from the image data, the face counting accumulator does not process, and the sum of the undetected face counting accumulator is increased by 1;
s2, registering a standard sitting posture;
s3, determining whether the registration is successful? If not, re-entering the step S2; if yes, carrying out the next step;
s4, processing the sitting posture calculation module again to obtain sitting posture information;
s5, comparing the real-time coordinate with the standard sitting posture deviation;
s6, determine whether the deviation exceeds a threshold? If not, re-entering the step S4; if the face counting accumulator is detected to be larger than the preset threshold value or not, the current sitting posture is considered to be abnormal, and the next step S7 is carried out;
s7, determine whether the state duration exceeds a specified period? If not, re-entering the step S4, and if so, performing the next step S8;
s8, judging whether a target exists or not:
judging a face counting accumulator, if the face counting accumulator is not more than 1, determining that no face is detected in the detection period, and determining that no target person is in the detection range of the detector, and performing the next step S9;
s9, alarming for sitting posture abnormity, and assigning Alarm =1;
s10, processing the sitting posture calculation module again to obtain sitting posture information;
s11, comparing the real-time coordinate with the standard coordinate deviation again;
s12, judging whether the sitting posture meets the standard? If not, re-entering the step S9; if yes, the Alarm is cancelled, alarm =0 is reset, and step S4 is re-entered.
2. The method of claim 1, wherein the processing sitting posture calculating module of step S1, S4 or S10 further comprises:
a, the face detection module obtains a face bounding box from image data;
b, deducting human face ROI data according to the human face boundary frame, transmitting the human face ROI data to a human face angle detection module, obtaining a human face space angle, and adding 1 to a human face counting accumulator;
and c, integrating the face bounding box to be obtained and the face space angle together by the sitting posture information calculating module, and updating the face counting accumulator and the undetected face counting accumulator for other modules to calculate.
3. The method of claim 1, wherein the step S2 of registering in a standard sitting posture further comprises: the sitting posture information data is obtained through the step S1, the sitting posture information data obtained by one frame of data is used as a result, and a preset number n of sitting posture information data results are continuously obtained, wherein n is a positive integer larger than or equal to 3.
4. The method as claimed in claim 3, wherein the step S2 further comprises: the condition for judging the success of registering the standard sitting posture is that,
1) At least 3 maximum values of the angle deviation values in the sitting posture information result are smaller than a preset first threshold value;
2) The spatial position deviation value meets a preset second threshold value;
3) The above two conditions 1) and 2) must be satisfied simultaneously, then the standard sitting posture registration is successful.
5. The method of claim 1, wherein comparing the real-time sitting posture with the standard sitting posture deviation in step S5 or S11 further comprises:
A. in the detection, acquiring sitting posture information of the current frame and performing deviation calculation on the registered sitting posture information;
B. and calculating a face space angle deviation value and a face space position deviation value.
6. The method as claimed in claim 1, wherein the step S6 of determining whether the deviation exceeds a threshold further comprises: and if one or both of the calculated face space angle deviation value and the calculated face space position deviation value exceed a preset threshold, performing the next step S7.
7. The method of claim 1, wherein the step S7 of determining whether the duration of the state exceeding the threshold exceeds a specified period further comprises: when the deviation exceeds a threshold value, starting to accumulate the number of the abnormal sitting posture frames when the sitting posture is abnormal and simultaneously starting to time, and when the abnormal sitting posture count exceeds a preset number in the specified period, confirming that the abnormal sitting posture is established, giving an alarm signal and carrying out the next step S8; otherwise, the information is considered to be false information, the step S4 is carried out again to process the sitting posture calculation module, and the sitting posture data information is continuously monitored.
8. The method of claim 7, wherein the predetermined number is a positive integer greater than 1.
9. The method for solving the problem of false Alarm generated when there is no target in front of the detector in sitting posture detection as claimed in claim 7, wherein the Alarm signal is given and Alarm =1.
10. The method for solving the false Alarm generated when there is no object in front of the detector in the sitting posture detection as claimed in claim 7, wherein in step S8, if it is determined that there is no object person in the detection range of the detector, the Alarm signal is cancelled and Alarm =0 is set; and if the face counting accumulator is larger than 1, the face is detected in the detection period, the target person is judged to be in the detection range of the detector, and the step S4 is carried out again.
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