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Video Scene Analysis: A Machine Learning Perspective

  • Wen Gao
  • Yonghong Tian
  • Lingyu Duan
  • Jia Li
  • Yuanning Li
Chapter

Abstract

With the increasing proliferation of digital video contents, learning-based video scene analysis has proven to be an effective methodology for improving the access and retrieval of large video collections. This chapter is devoted to present a survey and tutorial on the research in this topic. We identify two major categories of the state-of-the-art tasks based on their application setup and learning targets: generic methods and genre-specific analysis techniques. For generic video scene analysis problems, we discuss two kinds of learning models that aim at narrowing down the semantic gap and the intention gap, two main research challenges in video content analysis and retrieval. For genre-specific analysis problems, we take sports video analysis and surveillance event detection as illustrating examples.

Keywords

Visual Saliency Sport Video Video Annotation Shot Sequence Video Content Analysis 
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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Notes

Acknowledgements

The work is supported by grants from the Chinese National Natural Science Foundation under contract No. 60973055 and No. 61035001, and National Basic Research Program of China under contract No. 2009CB320906.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Wen Gao
    • 1
  • Yonghong Tian
  • Lingyu Duan
  • Jia Li
  • Yuanning Li
  1. 1.School of EE & CSPeking UniversityBeijingChina

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