@inbook {12497,
	title = {Statistical Analysis on Manifolds and Its Applications to Video Analysis},
	booktitle = {Video Search and MiningVideo Search and Mining},
	series = {Studies in Computational Intelligence},
	volume = {287},
	year = {2010},
	month = {2010///},
	pages = {115 - 144},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	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.},
	isbn = {978-3-642-12899-8},
	url = {http://dx.doi.org/10.1007/978-3-642-12900-1_5},
	author = {Turaga,Pavan and Veeraraghavan,Ashok and Srivastava,Anuj and Chellapa, Rama},
	editor = {Schonfeld,Dan and Shan,Caifeng and Tao,Dacheng and Wang,Liang}
}
