방송공학회논문지 (Journal of Broadcast Engineering)

  • 제13권5호
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  • Pages.681-684
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  • 2008
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  • 1226-7953(pISSN)
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  • 2287-9137(eISSN)
한국방송∙미디어공학회 (The Korean Institute of Broadcast and Media Engineers)
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Object Detection by Gaussian Mixture Model and Shape Adaptive Bidirectional Block Matching Algorithm

  • 박구만 (서울산업대학교 매체공학과) ;
  • ;
  • ;
  • Park, Goo-Man (Dept. of Media Engineering, Seoul National University of Technology) ;
  • Han, Byung-Wan (Dept. of Computer Animation, Tongwon College) ;
  • An, Tae-Ki (Korea Railroad Research Institute) ;
  • Lee, Kwang-Jeek (Dept. of Media Engineering, Seoul National University of Technology)
  • 발행 : 2008.09.30
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초록

We proposed a method to improve moving object detection capability of Gaussian Mixture Model by suggesting shape adaptive bidirectional block matching algorithm. This method achieves more accurate detection and tracking performance at various motion types such as slow, fast, and bimodal motions than that of Gaussian Mixture Model. Experimental results showed that the proposed method outperformed the conventional methods.

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참고문헌

  1. A.Gyaourova, C.kamath, and S.-C. Cheung, "Block Matching for Object Tracking,"Technical Report, Lawrence Livermore National Laboratory, UCRL-TR-200271, Oct.14, 2003
  2. Ivan Laptev, et. al., "Local velocity-adapted motion events for spatio-temporal recognition," Computer Vision and Image Understanding,vol108, No.3,108, pp.207-229, Dec.,2007 https://doi.org/10.1016/j.cviu.2006.11.023
  3. C. Stauffer, W.E.L. Grimson, "Adaptive Background Mixture Mo- dels for Real-time Tracking," Proc.IEEE Conference on Computer Vision & Pattern Recognition, vol.2, pp.246-252, June, 1999