Compressed telesurveillance video database retrieval using fuzzy classification system

  • Authors:
  • Samia F. Khelifi;M. Elarbi Boudihir;Rachid Nourine

  • Affiliations:
  • ICEPS Laboratory. Research Centre, Algeria;Dept. Computer Sciences and Information System, M. Ibn Saoud University, Er Riad;ICEPS Laboratory. Research Centre, Algeria

  • Venue:
  • ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
  • Year:
  • 2005

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Abstract

This paper proposes a video retrieval system from compressed outdoor video surveillance databases. The aim is to extract moving objects from frames provided by MPEG video stream in order to classify them into predefined categories according to image-based properties, and then robustly index them. The principal idea is to combine between useful properties of metrical classification and the notion of temporal consistency. Fuzzy geometry classification is used in order to provide an efficient method to classify motion regions into three generic categories: pedestrian, vehicle and no identified object. The temporal consistency provides a robust classification to changes of objects appearance and occlusion of object motion. The classified motion regions are used as templates for metrical training algorithms and as keys for tree indexing technique.