OpenCV(open source computer vision library)-based video target tracking algorithm

Abstract

The invention discloses an openCV(open source computer vision library)-based video target tracking algorithm. The openCV-based video target tracking algorithm is characterized in that a selected template is matched with a video frame; a subgraph position which is most similar to a template image in the video frame is found out through calculation of correlative coefficients; updating of the template is determined according to a predicted position of a kalman filter and the correlative coefficient values; and the specific algorithm includes template matching, position prediction and template updating. Compared with the prior art, the openCV-based video target tracking algorithm has the advantages that recognition and tracking of a target are not affected by environment change; the target object is accurately recognized and tracked in time; and the updating of the tracked object is available, so that the template can be dynamically updated during the system tracking, and the tracking is more accurate under the condition of environment and object change. In addition, a plurality of parameters are used as tracking evidences, so that the tracking is more reliable; and under the condition of target object moving, continuous background change and shadow influence, the tracking object cannot be lost..

Description

technical field [0001] The invention relates to the technical field of video data analysis, in particular to an OpenCV-based video target tracking algorithm for image capture and video data analysis. Background technique [0002] Video tracking is a research direction emerging in recent years. The algorithm of video tracking takes image sequence as input, and the output is various attributes of the target in the image, such as the size and position of the target. Under ideal conditions, these outputs are accurate and real-time. However, in the real world, due to the existence of various interferences, it is often difficult to achieve the ideal state. Therefore, whether the interference can be eliminated and the target object can be accurately captured is a measure of video tracking. The key to the quality of the algorithm. [0003] At present, the commonly used video tracking algorithms are as follows: [0004] (1) The Meanshift algorithm is a method that uses color inform...

AI Technical Summary

Problems solved by technology

[0007] To sum up, the problems existing in the existing technology are: the recognition and tracking of targets is greatly affected by environmental changes, and does not support the updating of tracked objects; relying only on a single or small amount of information as a tracking standard is not accurate enough. It is easier to lose track or mistrack when the target is constantly changing

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