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A Novel Framework for Robust Annotation and Retrieval in Video Sequences

  • Arasanathan Anjulan
  • Nishan Canagarajah
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4071)

Abstract

This paper describes a method for automatic video annotation and scene retrieval based on local region descriptors. A novel framework is proposed for combined video segmentation, content extraction and retrieval. A similarity measure, previously proposed by the authors based on local region features, is used for video segmentation. The local regions are tracked throughout a shot and stable features are extracted. The conventional key frame method is replaced with these stable local features to characterise different shots. Compared to previous video annotation approaches, the proposed method is highly robust to camera and object motions and can withstand severe illumination changes and spatial editing. We apply the proposed framework to shot cut detection and scene retrieval applications and demonstrate superior performance compared to existing methods. Furthermore as segmentation and content extraction are performed within the same step, the overall computational complexity of the system is considerably reduced.

Keywords

Video Sequence Video Segmentation Video Annotation Maximally Stable Extremal Region Region Descriptor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Arasanathan Anjulan
    • 1
  • Nishan Canagarajah
    • 1
  1. 1.Department of Electrical and Electronic EngineeringUniversity of BristolBristolUK

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