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  • Research Article
  • Open Access

Multiple Moving Object Detection for Fast Video Content Description in Compressed Domain

  • 1,
  • 2Email author,
  • 1 and
  • 2
EURASIP Journal on Advances in Signal Processing20072008:231930

  • Received: 20 November 2006
  • Accepted: 20 August 2007
  • Published:


Indexing deals with the automatic extraction of information with the objective of automatically describing and organizing the content. Thinking of a video stream, different types of information can be considered semantically important. Since we can assume that the most relevant one is linked to the presence of moving foreground objects, their number, their shape, and their appearance can constitute a good mean for content description. For this reason, we propose to combine both motion information and region-based color segmentation to extract moving objects from an MPEG2 compressed video stream starting only considering low-resolution data. This approach, which we refer to as "rough indexing," consists in processing P-frame motion information first, and then in performing I-frame color segmentation. Next, since many details can be lost due to the low-resolution data, to improve the object detection results, a novel spatiotemporal filtering has been developed which is constituted by a quadric surface modeling the object trace along time. This method enables to effectively correct possible former detection errors without heavily increasing the computational effort.


  • Object Detection
  • Video Stream
  • Video Content
  • Motion Information
  • Foreground Object

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Authors’ Affiliations

Department of Electronics for Automations (DEA), University of Brescia, Brescia, 25123, Italy
Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université Bordeaux 1/Bordeaux 2/CNRS/ENSEIRB, Talence Cedex, 33405, France


© Francesca Manerba et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.