Real-time moving object segmentation in H.264 compressed domain based on approximate reasoning

  • Authors:

  • C. Solana-Cipres;G. Fernandez-Escribano;L. Rodriguez-Benitez;J. Moreno-Garcia;L. Jimenez-Linares

  • Affiliations:

  • ORETO Research Group, University of Castilla-La Mancha, Tecnologias y Sistemas de Informacion, Paseo de la Universidad s/n, 13071 Ciudad Real, Spain;Instituto de Investigacion en Informatica, Campus Universitario s/n, 02071 Albacete, Spain;ORETO Research Group, University of Castilla-La Mancha, Tecnologias y Sistemas de Informacion, Paseo de la Universidad s/n, 13071 Ciudad Real, Spain;Escuela Ingenieria Tecnica Industrial, Avda. Carlos III s/n, 45071 Toledo, Spain;ORETO Research Group, University of Castilla-La Mancha, Tecnologias y Sistemas de Informacion, Paseo de la Universidad s/n, 13071 Ciudad Real, Spain

  • Venue:
  • International Journal of Approximate Reasoning
  • Year:
  • 2009

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Abstract

This paper presents a real-time segmentation algorithm to obtain moving objects from the H.264 compressed domain. The proposed segmentation works with very little information and is based on two features of the H.264 compressed video: motion vectors associated to the macroblocks and decision modes. The algorithm uses fuzzy logic and allows to describe position, velocity and size of the detected regions in a comprehensive way, so the proposed approach works with low level information but manages highly comprehensive linguistic concepts. The performance of the algorithm is improved using dynamic design of fuzzy sets that avoids merge and split problems. Experimental results for several traffic scenes demonstrate the real-time performance and the encouraging results in diverse situations.