TR2010-022

Statistical Analysis on Manifolds and Its Applications to Video Analysis

    •  Turaga, P., Veeraraghavan, A.N., Srivastava, A., Chellappa, R., "Statistical Analysis on Manifolds and Its Applications to Video Analysis" in Video Search and Mining, DOI: 10.1007/​978-3-642-12900-1_5, vol. 287, pp. 115-144, Springer, April 2010.
      BibTeX TR2010-022 PDF
      • @incollection{Turaga2010apr,
      • author = {Turaga, P. and Veeraraghavan, A.N. and Srivastava, A. and Chellappa, R.},
      • title = {Statistical Analysis on Manifolds and Its Applications to Video Analysis},
      • booktitle = {Video Search and Mining},
      • year = 2010,
      • volume = 287,
      • pages = {115--144},
      • month = apr,
      • publisher = {Springer},
      • doi = {10.1007/978-3-642-12900-1_5},
      • issn = {1860-949X},
      • url = {https://www.merl.com/publications/TR2010-022}
      • }
  • Research Area:

    Computer Vision

Abstract:

The analysis and interpretation of video data is an important component of modern vision applications such as biometrics, surveillance, motionsynthesis and web-based user interfaces. A common requirement among these very different applications is the ability to learn statistical models of appearance and motion from a collection of videos, and then use them for recognizing actions or persons in a new video. These applications in video analysis require statistical inference methods to be devised on non-Euclidean spaces or more formally on manifolds. This chapter outlines a broad survey of applications in video analysis that involve manifolds. We develop the required mathematical tools needed to perform statistical inference on manifolds and show their effectiveness in real video-understanding applications.

 

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