Occlusion detection using horizontally segmented windows for vehicle tracking

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• 作者：Ahra Jo (1)
  Gil-Jin Jang (1)
  Bohyung Han (2)
  
  1. School of of Electrical and Computer Engineering ; Ulsan National Institute of Science and Technology (UNIST) ; Ulsan ; 689-798 ; Republic of Korea
  2. Department of Computer Science and Engineering ; Pohang University of Science and Technology (POSTECH) ; Pohang ; 790-784 ; Republic of Korea
  
• 关键词：Computer vision ; Object tracking ; Particle filters ; Occlusion detection ; Histogram similarity
• 刊名：Multimedia Tools and Applications
• 出版年：2015
• 出版时间：January 2015
• 年：2015
• 卷：74
• 期：1
• 页码：227-243
• 全文大小：1,873 KB
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• 刊物类别：Computer Science
• 刊物主题：Multimedia Information Systems
  Computer Communication Networks
  Data Structures, Cryptology and Information Theory
  Special Purpose and Application-Based Systems
  
• 出版者：Springer Netherlands
• ISSN：1573-7721

文摘

This paper proposes an efficient algorithm for detecting occlusions in a video sequences of ground vehicles using color information. The proposed method uses a rectangular window to track a target vehicle, and the window is horizontally divided into several sub-regions of equal width. Each region is determined to be occluded or not based on the color histogram similarity to the corresponding region of the target. The occlusion detection results are used in likelihood computation of the conventional tracking algorithm based on particle filtering. Experimental results in real scenes show that the proposed method finds the occluded region successfully and improves the performance of the conventional trackers.