Front side gait cycle detecting method based on video

Abstract

The invention provides a front side gait cycle detecting method based on video, which comprises the target profile capture of a pedestrian and the cycle detection of a front side gait. Firstly, a single-frame image is extracted from the video, and is treated by gray level transformation, and then an image without a human body is used as the original background image of the whole video; secondly, a human body target is extracted by adopting a background deduction method with a real-time updated background, and binarization treatment is carried out on an image sequence by a Kapur entropy threshold method; thirdly, the vacancy of the binarized image is filled up by mathematical morphology, a human silhouette is extracted and analyzed by single communication so as to centralize the human body, and all the sizes of the images are 64*64 pixels; finally, the extracted human body is detected, the redundant frames containing an incomplete human body are eliminated, and the number change of the pixels of a lower arm swinging area is used as the basis for judging the front side gait cycle according to the relation of the proportion of the limbs to a body height. The invention has significant effect on the detection of the front side gait cycle, and the amount of calculation is small, thereby saving a large amount of storage space so as to make real-time gait identification possible.

Description

(1) Technical field [0001] The invention relates to a pattern recognition technology, in particular to a video-based frontal gait cycle detection method. (2) Background technology [0002] Gait refers to the posture in which people walk, and is the only perceivable biological behavioral characteristic at long distances. It achieves the purpose of identifying people by walking. We all know that people walk in different ways and that the movements of their feet and the rest of their body are unique. Moreover, this posture is relatively stable, and it is not easy to change in a certain time range and under the same walking environment, and people can judge the identity of the traveler accordingly. Gait recognition has the advantages of non-invasive, non-contact, difficult to hide and camouflage, easy to collect, and long-distance. Gait recognition research is a popular research topic in the field of computer vision and pattern recognition in recent years. It has great theore...

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Problems solved by technology

BenAbdelkader also determined the gait cycle by calculating the width change of the bounding rectangle of the human body outline; Collins et al. analyzed the periodic changes in the height and width of the human body, and then observed the gait cycle; Kale et al. observed the norm of the human body width vector The periodic characteristics of the gait are analyzed over time; however, the width of the frontal gait remains basically constant, so these methods cannot be used for periodic detection of the frontal gait

Sarkar et al. used the periodic characteristics of the number of pixels in the lower half of the human body area to determine the periodic change of gait; Chen Shi et al. used the rectangular frame outside the outline area of ​​all pedestrians in the gait sequence as the image area, and in the image area from bottom to bottom In the upper 1 / 4 height, divide the three areas equally horizontally, calculate the cumulative contour points of each area, and obtain the corresponding point distribution histogram feature to detect the gait cycle; but the legs and feet are seriously affected by the shadow of the person, and the Does not apply to period determination for frontal gait

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