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Content-based video object segmentation technology

Author: HuangZhiLi
Tutor: HaoZhongYang
School: Northwestern Polytechnical University
Course: Signal and Information Processing
Keywords: MPEG-4 standard Video Coding Object-oriented Video object Video object segmentation Head-and-shoulders video sequence Pyramid theory
CLC: TN911.73
Type: Master's thesis
Year: 2005
Downloads: 149
Quote: 0
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Abstract


Content - based video object segmentation is a hot research topic in digital video technology and even the field of computer vision . MPEG-4 video object is defined , but so far there is no specific definition video object segmentation method , therefore, become the content of the research paper . The main work of the paper include : ● video object segmentation techniques discussed in detail the status quo , and several representative depth analysis, discussion and compare their advantages and disadvantages , and the scope of application ; ● in-depth study on video objects split to extract the necessary infrastructure technology ; innovation of the paper are : 1 . extraction algorithm proposed video object segmentation based on the edge of the block . Proved for the static background nod shoulder sequence video object segmentation problem , the proposed algorithm has better subjective visual segmentation . Avoid the traditional segmentation method some common problems , such as the problem of over-segmentation of the mathematical morphology based optical flow field equations instability and aperture . Successful introduction pyramid multiscale hierarchical theory of ideology , to each pixel macroblock layer by layer from the upper to the lower fine split mode . Claire sequence for the head and shoulders of the international generic video , video object segmentation average processing speed can be increased to 12 frames / sec , the ratio the international typical processing speed of the algorithm ( such as Kim 7 / of algorithm 4 / sec and Li algorithm seconds ) with a large degree of increase. 3 . Improve the traditional threshold selection method may provide a more appropriate threshold for image binarization . Misdetection or undetected pixels the number of blocks thus effectively be controlled at an average of about a .

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