Statistical analysis on manifolds and its applications to video analysis

Pavan Turaga, Ashok Veeraraghavan, Anuj Srivastava, Rama Chellappa

Research output: Chapter in Book/Report/Conference proceedingChapter

10 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationVideo Search and Mining
EditorsDan Schonfeld, Caifeng Shan, Dacheng Tao, Liang Wang
Pages115-144
Number of pages30
DOIs
StatePublished - 2010
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume287
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence

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