Detection and segmentation of moving objects in complex scenes

  • Authors:
  • Aurélie Bugeau;Patrick Pérez

  • Affiliations:
  • INRIA, Centre Rennes - Bretagne Atlantique, Campus de Beaulieu, 35 042 Rennes Cedex, France;INRIA, Centre Rennes - Bretagne Atlantique, Campus de Beaulieu, 35 042 Rennes Cedex, France

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2009

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Abstract

In this paper, we address the difficult task of detecting and segmenting foreground moving objects in complex scenes. The sequences we consider exhibit highly dynamic backgrounds, illumination changes and low contrasts, and can have been shot by a moving camera. Three main steps compose the proposed method. First, a set of moving points is selected within a sub-grid of image pixels. A multi-cue descriptor is associated to each of these points. Clusters of points are then formed using a variable bandwidth mean shift technique with automatic bandwidth selection. Finally, segmentation of the object associated to a given cluster is performed using graph cuts. Experiments and comparisons to other motion detection methods on challenging sequences demonstrate the performance of the proposed method for video analysis in complex scenes.