@inbook {12640,
	title = {Computer Vision, Statistics in},
	booktitle = {Encyclopedia of Statistical SciencesEncyclopedia of Statistical Sciences},
	year = {2006},
	month = {2006///},
	publisher = {John Wiley \& Sons, Inc.},
	organization = {John Wiley \& Sons, Inc.},
	abstract = {Computer Vision (CV) broadly refers to the discipline where extraction of useful 2D and/or 3D information from one or more images is of interest. Useful information could consist of features such as edges, lines, curves and textures, or information about depth, motion, object descriptions, etc. CV problems are usually ill-posed inverse problems. Since the image data is usually obtained from sensors such as video cameras, infrared, radar, etc., the information extraction processes often have to deal with data that is corrupted by noise from the sensors and the environment. Statistics can help in obtaining robust and accurate solutions to these inverse problems by modeling the noise processes. We present here a broad overview of the applications of statistics to different computer vision problems and explain in detail two particular applications, tracking and motion analysis, where statistical approaches have been used very successfully.},
	keywords = {Computer vision, sampling, Statistics, structure from motion, tracking},
	isbn = {9780471667193},
	url = {http://onlinelibrary.wiley.com/doi/10.1002/0471667196.ess3129/abstract},
	author = {Chellapa, Rama and Chowdhury,Amit K. Roy}
}
