Contour gradient-based target tracking method

Abstract

The invention particularly discloses a contour gradient-based target tracking method. The method comprises the steps of segmenting candidate targets in an initial frame of an input video or image sequence, and extracting a reference image; extracting a contour of the reference image to serve as a standard feature template, and performing scale and angle conversion to obtain a multi-scale and multi-angle template sequence; from the next frame of the input video or image sequence, extracting gradient features of a target image; performing sliding window scanning based on a step length of 1 for the multi-scale and multi-angle template sequence on a feature image of the target image, and calculating the similarity of matching between the multi-scale and multi-angle template sequence and the feature image; according to information such as a matching position, a scale factor, an angle factor and the like, segmenting out a sub-region where a target is located in the target image to serve as areference image for the next detection to perform update; and repeating the steps until all the frames of the video or image sequence are detected. The invention aims to provide the contour gradient-based target tracking method for adapting to scale change and/or angle change of the target and improving target tracking accuracy.

Description

technical field [0001] The invention belongs to the technical field of computer image processing, and specifically discloses an object tracking method based on contour gradients. Background technique [0002] In security monitoring tasks, in order to achieve the requirement of automatic target tracking, it is often necessary to determine the target position of the region of interest in the video or continuous image sequence, and correspond to the target position in each frame of image. [0003] The research content of target tracking technology is mainly divided into the following two aspects: 1. To detect, track, identify and extract the required information for the moving target in the captured video sequence, such as the trajectory of the target and related motion parameters such as speed, acceleration, position, etc. Second, use the acquired motion parameters to predict and estimate the target to assist in decision-making. Therefore, the precise extraction of the featu...

AI Technical Summary

Problems solved by technology

[0012] (2) The feature points of the obtained reference image are arbitrarily large, usually contain less image information, cannot represent image features well, and the reliability and stability are not high, so the tracking algorithm does not have good robustness

[0013] (3) It is difficult to achieve real-time feature matching calculation, which affects the response speed of target tracking

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