Real-time target tracking method based on online study

Abstract

The invention discloses a real-time target tracking method based on online study. Through structuring a video collecting module, an ELM classifier initial training module, a target tracking module, a classifier updating module and a video storage module, the real-time target tracking method based on online study is realized. The video collecting module reads image data, the ELM classifier initial training module forms an initial ELM classifier, and the target tracking module tracks and positions the target; the ELM classifier updating module updates the ELM classifier and the video storage module to compress and encode the video. A target location based on a particle filter uses limited particle number to generate candidate samples, thus the calculation amount is reduced, and the calculating efficiency is improved; the ELM classifier based on the online study realizes the real-time gain study of the training sample, rapidly adapts to the target appearance change, and promotes the target tracking precision.

Description

technical field [0001] The invention relates to a target tracking method, in particular to a real-time target tracking method based on online learning. Background technique [0002] In recent years, in order to solve the problem of target tracking, many scholars have applied target classification methods to target tracking. Such methods regard target tracking as a binary classification problem, and separate the target from the background by training a classifier. For example, support vector machine, that is, Support vector machine, SVM combined with optical flow method, is used to track vehicle targets. This method needs to collect a large number of vehicle samples and non-vehicle samples to train the support vector machine before tracking, and combine the optical flow method in each frame image to obtain the precise position of the target. The difficulty of this method lies in the formation and training of a large number of positive and negative samples. There is also a s...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a real-time target tracking method based on online learning, which solves the problems of difficulty in constructing target tracking samples in traditional classification methods, large classifier errors, large amount of calculations for online update of classifiers and exhaustive search and positioning

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