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Video sequences target tracking technology

Author: YanZuYang
Tutor: RenQingSheng
School: Shanghai Jiaotong University
Course: Applied Computer Technology
Keywords: Particle filter Integrated Learning Tracking Trust propagation
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 73
Quote: 2
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Abstract


Target tracking is one of the hotspots of computer vision , such as it is in human-computer interaction , automatic navigation , virtual reality , medical diagnostics , auto focus and many other areas all have broad application prospects . The main work in the following aspects : First, discuss the particle filter framework to calculate the probability of observing a function of two specific calculation method: integrated learning methods and outline methods . In the main concepts of integrated learning method is a set of weak classifiers constitute constitute strong classifier and obtain a new sample is continuously updated weak classifiers . In the video tracking problem , we use the integrated learning approach at the pixel level classification of the target and the background and get contents after an update classifier . This article also discusses some improvements ensemble learning methods , including the use of a weak way of learning weak classifiers to be updated. Experimental results show that the improved integration of learning methods to better adapt to changes in the target and the surrounding background . We also made observations with the outline feature calculation method of the probability function . This method can have a fixed target contour tracking effectively , even in the event of severe occlusion illumination changes and circumstances, can still maintain a high accuracy . Second, the belief propagation algorithm and its environment in the timing on the particle filter algorithm implementation. We will strengthen the belief propagation algorithm is applied separately to a single target tracking multiple targets tracking performance and reduce the interference factor. First, we will trust propagation algorithm used in conjunction with a number of different target tracking feature . Experiments show that trust propagation algorithm combined with multiple features superior tracking algorithm using only a single feature tracking algorithm . We will then physically introduced the concept of magnetic and inertial frame to trust propagation algorithm proposed magnetic inertial trust propagation algorithm . Experimental results show that the algorithm for multi- target tracking occurs when each block is very robust .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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