Target tracking method based on improved particle filter algorithm

Abstract

The invention relates to a target tracking method based on an improved particle filter algorithm. The target tracking method includes the steps: reading a first frame image after acquiring a video stream; selecting tracked targets, and performing multi-dimensional feature extraction, establishing a target template, reading a next frame of image, performing target search by using the target template, performing weighted resampling on a searched target, performing interference detection, if interference exists, performing correction, otherwise, directly determining whether a target template updating condition is triggered; and if so, updating the target template and continuing target tracking. According to the target tracking method, the traditional particle filtering algorithm is improved from four aspects of increasing the feature dimension, reducing the particle attenuation, improving the algorithm immunity and introducing the target template updating strategy, and the target can be effectively tracked under the condition that the tracking environment is migrated and the interference of similar targets and shielding objects occurs, and the requirement of the real-time performanceof the system is met.

Description

technical field [0001] The present invention relates to the technical field of data identification; data representation; record carrier; record carrier processing, in particular to a target tracking method based on an improved particle filter algorithm. Background technique [0002] Moving object detection is one of the important research directions of video analysis technology research. It has a wide range of applications and is closely related to people's lives. For example, in an intelligent surveillance system, accurate object tracking is a prerequisite for detecting and analyzing abnormal behaviors of designated pedestrians. [0003] In video analysis technology, target tracking is the process of searching and extracting target features in video frames and matching them with target templates. According to the type of matching target template, the moving target tracking algorithm includes the following categories, and its defects are also very obvious. [0004] Tracking...

AI Technical Summary

Problems solved by technology

[0013] There are some defects in the traditional particle filter algorithm itself, the main problem is: first, the use of a single color feature as the target template leads to poor tracking stability; Accuracy; at the same time, the traditional particle filter algorithm, as an area-based target tracking algorithm, has a common problem with the area-based target tracking algorithm, that is, the tracking effect will become poor when the target is occluded

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