CN103049788A - Computer-vision-based system and method for detecting number of pedestrians waiting to cross crosswalk - Google Patents
Computer-vision-based system and method for detecting number of pedestrians waiting to cross crosswalk Download PDFInfo
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Abstract
The invention relates to a computer-vision-based system and method for detecting the number of pedestrians waiting to cross a crosswalk. The system comprises two charge coupled device (CCD) cameras and a computer image processing system, wherein the computer image processing system is connected with the cameras through interfaces; the two CCD cameras are arranged at two ends of the crosswalk; and field angles of the two CCD cameras cover an opposite pedestrian waiting region and a diagonally opposite vehicle region. The method comprises the following steps of: acquiring an image from a video image; preprocessing the pedestrian waiting region; acquiring a foreground image by using a Gaussian mixed background model method; acquiring a vertical integral projection graph; and processing the vertical integral projection graph, and performing information statistics to obtain the number of the pedestrians waiting to cross the crosswalk. Compared with a conventional pedestrian number detection method, the method has the advantages of simplicity and high efficiency, and can be applied to a complicated situation.
Description
Technical field
The present invention relates to technical field of computer vision, specifically treat space number purpose detection method based on the crossing of computer vision.
Background technology
At present, in intelligent transportation and computer vision field, pedestrian's determination and analysis is a part and parcel.Pedestrian's detection and analytical technology after deliberation more than ten years, but still the neither one standard is accurate, high performance, and real-time pedestrian detection and analytical algorithm.Since some intrinsic characteristics of pedestrian, the complicacy of application scenarios, and influencing each other between person to person or the human and environment is so that pedestrian's determination and analysis is the most difficult in a computer vision research field challenge.
In in the past more than ten years, pay close attention to widely and study and produced many existing detection methods in the situation that pedestrian detection technology has obtained academia and engineering circles, utilize the contour feature of human body to detect the pedestrian such as people such as Haritaoglu Gavrila, because human body presents certain symmetry at body centre's axis coordinate, therefore, can calculate certain regional internal object profile at the projection histogram of horizontal and vertical directions, analyze symmetry, to determine that whether target is as the pedestrian.Rivlin, the people such as Senior will be mated with an ellipse through the target after the motion segmentation, oval major and minor axis and length ratio thereof, and the angle that forms between plane of delineation coordinate system of major and minor axis can be used as shape facility the pedestrian is classified.The people such as Lipton have defined the dispersion that is compared to of moving target rim circumference square and area, utilize this feature to distinguish the objects such as pedestrian, automobile.The people such as Collins have been merged above a plurality of parameters, and the area of use target, length breadth ratio, dispersion etc. have trained a three-layer neural network that the targets such as pedestrian, vehicle and crowd are classified as feature.All there are some defectives in above these four methods, at first, than the impact that is easier to be subject to noise, pedestrian's action variation, the complexity of background, extraction that all can destructive characteristics.Secondly, for shape facility, owing to being that the foreground area of cutting apart is analyzed, therefore, they extremely rely on the performance of dispenser, and the background segment technology still exists many problems to need to solve.
Summary of the invention
Be not suitable for the problem of the pedestrian detection in the complex environment for the method for the existing detection number of people, the invention provides a kind of crossing and treat space number purpose detection method, the number that detects the pedestrian that not only can be more accurate, and it is simply effective, goes for comparatively complex environment.
The present invention is achieved by the following technical solutions:
The space number for the treatment of purpose detection system based on computer vision comprises two ccd video cameras and Computerized image processing system; Described Computerized image processing system links to each other with video camera by interface; Described two ccd video cameras are installed on the two ends of crossing; The field angle of described two ccd video cameras comprises the wait pedestrian zone on opposite and the vehicle region at opposite slightly to the right or left.
Detection method based on the space number of the treating purpose detection system of computer vision may further comprise the steps:
1) video camera capture video images;
2) image in the video image is carried out cutting apart and light intensity adaptive change pre-service of pedestrian's waiting area;
3) adopt based on Gaussian mixture model-universal background model method realization context update, and obtain the foreground picture of pedestrian's waiting area and it is carried out pre-service;
4) based on the method for vertical integral projection pretreated foreground picture is processed to obtain the vertical integral projection figure of pedestrian's waiting area;
5) treat number by the pedestrian by the processing of the vertical integral projection figure of pedestrian's waiting area and Information Statistics finally being obtained crossing.
Abovementioned steps 2) light intensity adaptive change pre-service comprises in,
2-1) coloured image with every two field picture of camera acquisition is converted into gray level image;
2-2) add up according to grey level histogram, judge the intensity of light in the image and the contrast of image;
Getting the gray level statistics is
Wherein, H
iBe the probability that each gray level occurs, i is gray level progression;
If 2-3) L 〉=O.8 or L≤0.2 are to the adjustment of current frame image degree of comparing.
Abovementioned steps 3) chooses in when the pedestrian begins by lateral road and begin to upgrade background, extract foreground picture during 1s before being chosen in vehicle pass-through and finishing ~ 2s.
Abovementioned steps 3) pre-service of foreground picture is for to carry out successively histogram equalization to foreground image in, medium filtering, connected domain denoising, expansive working.
Abovementioned steps 4) in, vertically integral projection V is,
Wherein P (i, j) the expression foreground picture pixel value corresponding with the i position is that 0 pixel is counted, and W is the width of pretreated image, and H is the height of pretreated image.
Abovementioned steps 5) comprise,
5-1) delimit threshold line, be the vertical zone in the potential zone of the number of people greater than the line point of threshold value, and remove the point in the potential zone of the non-number of people;
The threshold value of 5-2) delimiting the potential zone of the number of people is removed noise spot;
5-3) to the width in effective vertically zone with highly add up, determine width that people is shared and highly;
5-4) with every effectively vertically the width in zone and height with obtain this time detect in the shared width of people and highly comparing, determine the contained number in this zone;
5-5) will count every effectively vertically the quantity of the pedestrian in the zone all add up, as this detect the final wait of obtaining pedestrian's the quantity of lateral road.
Abovementioned steps 5-1) the delimitation threshold line is adaptive the looking for of distribution situation according to the integral projection of vertical direction in
To a rational threshold value Threshold,
P wherein
iBe V
(i), the probability of i ∈ [1, W], α are scale factor, α ∈ [0.6,1].
Abovementioned steps 5-2) threshold value in is 20 pixels.
Abovementioned steps 5-3) refers to: to the width in effective vertically zone with highly add up, obtain first minimum width and height, again on this basis, by with minimum value differ mean value less than the value of 5 pixels determine this time to detect in width and the height that the people is shared.
Abovementioned steps 5-4) refer to:
If one vertically the zone surpass the shared width of people and highly all in the threshold value allowed band then should only comprise a pedestrian in the zone;
When the vertical zone value outside the threshold value allowed band time that surpasses the shared width of people and height, only width surpasses then two pedestrians of this district inclusion of the shared width of people, only highly surpass then two pedestrians of this district inclusion of the shared height of people, if width and highly all above the shared width of people and four pedestrians of this district inclusion highly then.
The threshold value of aforesaid threshold values allowed band arranges according to the position that concrete condition and the video camera at crossing sets up.
The height threshold of aforesaid threshold values is 12 pixels, and width threshold value is 17 pixels.
Advantage of the present invention is, method is simply effective, comparing detection people counting method based on characteristic matching easily is subject to the ambient soma and disturbs the larger situation of error under the complex situations that makes, the present invention is more suitable for operating under complicated situation, the intelligent traffic light supervisory systems that applies to the crossing place is particularly suitable, because principle is simple, reduction cost that also can be suitable.
Description of drawings
Fig. 1 is that the crossing that the present invention is based on computer vision is treated space number purpose detection method process flow diagram;
Fig. 2 is that the present invention is to processing and the Information Statistics analysis process figure of vertical integral projection figure.
Embodiment
The present invention is further described below in conjunction with the drawings and specific embodiments.
The space number for the treatment of purpose detection system based on computer vision comprises two ccd video cameras and Computerized image processing system; Described Computerized image processing system links to each other with video camera by interface; Described two ccd video cameras are installed on the two ends of crossing; The field angle of described two ccd video cameras comprises the wait pedestrian zone on opposite and the vehicle region at opposite slightly to the right or left.
As shown in Figure 1, treat the detection method of space number purpose detection system based on the crossing of computer vision, may further comprise the steps:
1) video camera capture video images;
2) image in the video image is carried out cutting apart and light intensity adaptive change pre-service of pedestrian's waiting area;
3) employing obtains the foreground picture of pedestrian's waiting area and it is carried out pre-service based on the Gaussian mixture model-universal background model method;
4) based on the method for vertical integral projection pretreated foreground picture is processed to obtain the vertical integral projection figure of pedestrian's waiting area;
5) treat number by the pedestrian by the processing of the vertical integral projection figure of pedestrian's waiting area and Information Statistics finally being obtained crossing.
Specifically be divided into following four parts:
First gets the image that obtains in the video image and carries out cutting apart and the pre-service such as light intensity adaptive change of pedestrian's waiting area, specifically may further comprise the steps:
(1) pedestrian stands cutting apart of zone.The maximum characteristics of image are the information that can provide a large amount of, meanwhile also can bring a large amount of interfere informations.Being partitioned into the stand purpose in zone of pedestrian from image is that the effective coverage that the pedestrian stands is extracted, and reduces to a certain extent simultaneously the part interfere information.
(2) light intensity adaptive change.For concrete crossing, owing to the light that the reasons such as weather cause is strong and weak different, bring very large inconvenience can for pedestrian's detection.When light in the sequence of video images was very weak or very strong, target and background had very large similarity, carried out in the gray-scale map that the frame-to-frame differences computing obtains, and target is not easy to be detected, and the impact of noise is also relatively large.So after being partitioned into pedestrian's the zone of standing, (picture traverse is W to the every two field picture that at first ccd video camera is gathered, highly for H) coloured image be converted into gray level image, then add up according to grey level histogram, judge the power of light in the image and the contrast of image, weak or stronger image carries out processing based on pixel in order to reach the purpose of figure image intensifying to light, concrete deterministic process is as follows: if present frame gray scale picture, I (x, y), add up the probability H that each gray level occurs
i, the gray level statistics is taken as:
If L 〉=O.8 or L≤0.2 are to the adjustment of current frame image degree of comparing.
Second portion adopts to obtain the foreground picture of pedestrian's waiting area and it is carried out pre-service based on the Gaussian mixture model-universal background model method, specifically may further comprise the steps:
(1) real-time update of background.The method of employing mixture Gaussian background model realizes the real-time update of background, add up by the frequency that the corresponding grey scale value to each pixel in the continuous multiple frames image occurs, when detected target is in the process of motion, in all gray-scale values that same pixel place occurs, the number of times that the gray-scale value of the pixel in the background image occurs therein is maximum, the frequency of occurrences that is other gray-scale values of frequency ratio of occurring of the gray-scale value of the pixel in the background image wants high, according to this principle, after statistics finishes, the gray-scale value that the frequency of occurrences is the highest is preserved as the gray-scale value at corresponding pixel points place, restore again the view picture background image, preserve at last this background image for future use.Stand the opportunity that regional background upgrades for the pedestrian, through lot of experiments, finally select when the pedestrian begins by lateral road, to begin to upgrade background (a bit of time can suitably be postponed), and should pass through the time (because in last 1 to 2 second in the pedestrian who sets a little earlier the closing time of context update, the pedestrian may stop and wait for next time and pass through, if continue to upgrade background, the pedestrian that then may be stopped this moment is also as background).
(2) prospect of inclusion test object obtains.Be chosen in the very last seconds clock that vehicle pass-through will finish among the present invention, during such as 1s ~ 2s, obtain a two field picture that comprises the pedestrian, the pedestrian's who comprises in this two field picture quantity information is relatively near truth (time, the information that comprises in this width of cloth image was more near truth the closer to the time that vehicle pass-through finishes).It is poor that this two field picture that will obtain again and the background image that obtains are previously done frame, thereby obtain foreground image.
(3) to the pre-service of foreground image.For further reduce disturbance, the foreground image that obtains has been carried out pre-service, processing procedure is for to carry out successively histogram equalization to foreground image, medium filtering, connected domain denoising, expansive working.
Third part is processed to obtain the vertical integral projection figure of pedestrian's waiting area based on the method for the vertical integral projection foreground picture after to denoising.If obtaining size, pre-service is the binary map G of W*H, W is the width of pretreated image, H is the height of pretreated image, notice the equal vanishing of background and part target area at this moment, and in the binary map, the more part of pixel number from the vertical area part at the head place of human body, based on such analysis, is determined the vertical zone at number of people place substantially on the vertical direction according to the integral projection of figure G vertical direction.The integral projection of the vertical direction of note V presentation graphs G, V is a W dimensional vector, wherein
P (i, j) the expression foreground image pixel value corresponding with the i position is that 0 pixel is counted, and W is picture traverse, and H is picture altitude.
The 4th part, treat as shown in Figure 2, specifically to may further comprise the steps number by the pedestrian by the processing of the vertical integral projection figure of pedestrian's waiting area and Information Statistics finally being obtained crossing:
(1) delimit threshold line, determine the vertical zone in the potential zone of the number of people, and remove the point in the potential zone of the non-number of people.In order to determine the vertical zone at potential number of people place, the present invention finds a rational threshold value to mark off these zones according to the distribution situation of the integral projection of figure G vertical direction is adaptive, and method is: statistics V
(i), the probability distribution of i ∈ [1, W], note V
(i), the probability of i ∈ [1, W] is P
i, threshold value is taken as:
Be the average statistical part of threshold value amount of orientation V, wherein α is a scale factor, α ∈ [0.6,1], and its value is relevant with the brightness of collection image, and the grey level histogram of the present image that is obtained by statistics calculates.By a large amount of tests, L≤0.6, α gets 0.6, and in other situations, α gets the value of L, and effect is relatively good.
(2) delimiting the threshold value vertical zone that width is too little removes as noise spot.After obtaining the vertical zone at potential number of people place, through a large amount of tests, choose suitable threshold value, the vertical zone that width is too little is removed, in the present embodiment, threshold value is elected 20 pixels as, and the position that this threshold value need to be set up according to crossing situation and the video camera of reality is measured.
(3) to the width in effective vertically zone with highly add up, determine width that people is shared and highly.To the width in effective vertically zone with highly add up, obtain first minimum width and height, again on this basis, width and height that the people is shared during the mean value of obtaining with minimum value several values of be more or less the same (as differing less than 5 pixels) determines this time to detect.
(4) with every effectively vertically the width in zone and height with obtain this time detect in the shared width of people and highly comparing, determine the contained number in this zone.If in the time of relatively when the width in some zones or when highly surpassing in this detection of obtaining the shared width of people or highly certain threshold value, then think and do not only have a pedestrian in this vertical zone, determine the final number in this zone according to the difference of threshold value, the position that the setting of this threshold value need to be set up according to crossing situation and the video camera of reality is measured, in the present embodiment, height threshold is 12 pixels, width threshold value is 17 pixels, specifically adds up what method of every vertical regional contained number to be: one vertically the zone surpass the shared width of people and highly all only comprise a pedestrian thinking still that in the threshold value allowed band this zone be can be regarded as; And if the vertical zone value outside the threshold value allowed band time that surpasses the shared width of people and height, only width surpasses the shared width of people and then thinks two pedestrians of this district inclusion, only highly surpass the shared height of people and then think two pedestrians of this district inclusion, if width and highly all above the shared width of people with highly then think four pedestrians of this district inclusion.
(5) will count every effectively vertically the quantity of the pedestrian in the zone all add up, as this detect the final wait of obtaining pedestrian's the quantity of lateral road.
Claims (13)
1. based on the space number of the treating purpose detection system of computer vision, it is characterized in that: comprise two ccd video cameras and Computerized image processing system; Described Computerized image processing system links to each other with video camera by interface; Described two ccd video cameras are installed on the two ends of crossing; The field angle of described two ccd video cameras comprises the wait pedestrian zone on opposite and the vehicle region at opposite slightly to the right or left.
2. the detection method of the space number of the treating purpose detection system based on computer vision according to claim 1 is characterized in that: may further comprise the steps:
1) video camera capture video images;
2) image in the video image is carried out cutting apart and light intensity adaptive change pre-service of pedestrian's waiting area;
3) adopt based on Gaussian mixture model-universal background model method realization context update, and obtain the foreground picture of pedestrian's waiting area and it is carried out pre-service;
4) based on the method for vertical integral projection pretreated foreground picture is processed to obtain the vertical integral projection figure of pedestrian's waiting area;
5) treat number by the pedestrian by the processing of the vertical integral projection figure of pedestrian's waiting area and Information Statistics finally being obtained crossing.
3. detection method according to claim 2 is characterized in that: light intensity adaptive change pre-service comprises described step 2),
2-1) coloured image with every two field picture of camera acquisition is converted into gray level image;
2-2) add up according to grey level histogram, judge the intensity of light in the image and the contrast of image;
Getting the gray level statistics is
Wherein, H
iBe the probability that each gray level occurs, i is gray level progression;
If 2-3) L 〉=O.8 or L≤0.2 are to the adjustment of current frame image degree of comparing.
4. detection method according to claim 2 is characterized in that: in the described step 3), choose when the pedestrian begins by lateral road and begin to upgrade background, extract foreground picture during 1s before being chosen in vehicle pass-through and finishing ~ 2s.
5. detection method according to claim 2 is characterized in that: in the described step 3) pre-service of foreground picture for foreground image is carried out histogram equalization successively, medium filtering, connected domain denoising, expansive working.
6. detection method according to claim 2 is characterized in that: in the described step 4), vertically integral projection V is,
Wherein P (i, j) the expression foreground picture pixel value corresponding with the i position is that 0 pixel is counted, and W is the width of pretreated image, and H is the height of pretreated image.
7. detection method according to claim 2 is characterized in that: described step 5) comprises,
5-1) delimit threshold line, be the vertical zone in the potential zone of the number of people greater than the line point of threshold value, and remove the point in the potential zone of the non-number of people;
The threshold value of 5-2) delimiting the potential zone of the number of people is removed noise spot;
5-3) to the width in effective vertically zone with highly add up, determine width that people is shared and highly;
5-4) with every effectively vertically the width in zone and height with obtain this time detect in the shared width of people and highly comparing, determine the contained number in this zone;
5-5) will count every effectively vertically the quantity of the pedestrian in the zone all add up, as this detect the final wait of obtaining pedestrian's the quantity of lateral road.
8. detection method according to claim 7 is characterized in that: delimit threshold line described step 5-1)
To find a rational threshold value according to the distribution situation of the integral projection of vertical direction is adaptive
Threshold，
P wherein
iBe V
(i), the probability of i ∈ [1, W], α are scale factor, α ∈ [0.6,1].
9. detection method according to claim 7, it is characterized in that: the threshold value described step 5-2) is 20 pixels.
10. detection method according to claim 7, it is characterized in that: described step 5-3) refer to: to the width in effective vertically zone with highly add up, obtain first minimum width and height, again on this basis, by with minimum value differ mean value less than the value of 5 pixels determine this time to detect in width and the height that the people is shared.
11. detection method according to claim 7 is characterized in that: described step 5-4) refer to:
If one vertically the zone surpass the shared width of people and highly all in the threshold value allowed band then should only comprise a pedestrian in the zone;
When the vertical zone value outside the threshold value allowed band time that surpasses the shared width of people and height, only width surpasses then two pedestrians of this district inclusion of the shared width of people, only highly surpass then two pedestrians of this district inclusion of the shared height of people, if width and highly all above the shared width of people and four pedestrians of this district inclusion highly then.
12. detection method according to claim 11 is characterized in that: described threshold value arranges according to the position that concrete condition and the video camera at crossing sets up.
13. detection method according to claim 12 is characterized in that: the height threshold of described threshold value is 12 pixels, and width threshold value is 17 pixels.
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