Pedestrian detecting and tracking method based on multi-stage detection

Abstract

The invention provides a pedestrian detecting and tracking method based on multi-stage detection. The method comprises the following steps that 1), background frames are extracted and preprocessed; 2), foreground regions are extracted and labeled through a rectangular frame, current frames and the background image frames are used for carrying out difference, foreground information is extracted, binarization processing is carried out on the foreground information, all the communicated foreground regions are labeled through the outer contour, a minimum bounding rectangle is drawn for each contour region, size information of all the rectangles is recorded, a differential image gray value and a threshold value T are compared, parts larger than T are determined as motion object parts, or else the parts are background parts; 3), the external characteristics of pedestrians are utilized for judging target regions preliminarily; 4), statistics is made on the number of the rectangular regions Rn judged to be the similar target regions, a pedestrian detecting algorithm based on the HOG characteristics is adopted for ruling out non-target regions, and then the optical flow method is adopted for tracking the remaining target regions. According to the method, the calculation speed is high, the instantaneity is good, and the practicality is high.

Description

technical field [0001] The invention relates to the field of video recognition, in particular to a pedestrian detection and tracking method. Background technique [0002] The existing optical flow method realizes the target tracking process: 1) For the obtained video frame sequence, use a certain target detection method (traditionally optical flow detection) to detect possible foreground targets; 2) If a certain frame appears Foreground target, find its representative key feature points (can be generated randomly, or use corner points as feature points); 3) For any two adjacent video frames after that, find the key points that appeared in the previous frame The optimal position of the key feature point in the current frame, so as to obtain the position coordinates of the foreground target in the current frame. [0003] The optical flow method can assign a velocity vector to each pixel in the image, and then dynamically analyze the image according to the velocity vector char...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of the existing pedestrian detection and tracking method realized by the optical flow method, such as slow calculation speed, poor real-time performance, and po

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