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Occlusion detection using horizontally segmented windows for vehicle tracking

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Abstract

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.

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Authors and Affiliations

  1. School of of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 689-798, Republic of Korea

    Ahra Jo & Gil-Jin Jang

  2. Department of Computer Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 790-784, Republic of Korea

    Bohyung Han

Authors
  1. Ahra Jo
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  2. Gil-Jin Jang
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  3. Bohyung Han
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Corresponding author

Correspondence to Gil-Jin Jang.

Additional information

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (No. 2012-0008090), and by the Converging Research Center Program through the Ministry of Science, ICT and Future Planning, Korea (No. 2013K000359).

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Jo, A., Jang, GJ. & Han, B. Occlusion detection using horizontally segmented windows for vehicle tracking. Multimed Tools Appl 74, 227–243 (2015). https://doi.org/10.1007/s11042-013-1846-5

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