000			04142nam a22005415i 4500
001			978-0-387-29486-5
003			DE-He213
005			20250710083944.0
007			cr nn 008mamaa
008			100301s2006 xxu| s |||| 0|eng d
020			_a9780387294865 _a99780387294865
024	7		_a10.1007/978-0-387-29486-5 _2doi
082	0	4	_a006.4 _223
100	1		_aZhou, Shaohua Kevin. _eauthor.
245	1	0	_aUnconstrained Face Recognition _h[recurso electrónico] / _cby Shaohua Kevin Zhou, Rama Chellappa, Wenyi Zhao.
264		1	_aBoston, MA : _bSpringer US, _c2006.
300			_aXII, 244 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aInternational Series on Biometrics ; _v5
505	0		_aFundamentals, Preliminaries and Reviews -- Fundamentals -- Preliminaries and Reviews -- Face Recognition Under Variations -- Symmetric Shape from Shading -- Generalized Photometric Stereo -- Illuminating Light Field -- Facial Aging -- Face Recognition Via Kernel Learning -- Probabilistic Distances in Reproducing Kernel Hilbert Space -- Matrix-Based Kernel Subspace Analysis -- Face Tracking and Recognition from Videos -- Adaptive Visual Tracking -- Simultaneous Tracking and Recognition -- Probabilistic Identity Characterization -- Summary and Future Research Directions -- Summary and Future Research Directions.
520			_aAlthough face recognition has been actively studied over the past decade, the state-of-the-art recognition systems yield satisfactory performance only under controlled scenarios. Recognition accuracy degrades significantly when confronted with unconstrained situations. Examples of unconstrained conditions include illumination and pose variations, video sequences, expression, aging, and so on. Recently, researchers have begun to investigate face recognition under unconstrained conditions that is referred to as unconstrained face recognition. This volume provides a comprehensive view of unconstrained face recognition, especially face recognition from multiple still images and/or video sequences, assembling a collection of novel approaches able to recognize human faces under various unconstrained situations. The underlying basis of these approaches is that, unlike conventional face recognition algorithms, they exploit the inherent characteristics of the unconstrained situation and thus improve the recognition performance when compared with conventional algorithms. Unconstrained Face Recognition is accessible to a wide audience with an elementary level of linear algebra, probability and statistics, and signal processing. Unconstrained Face Recognition is designed primarily for a professional audience composed of practitioners and researchers working within face recognition and other biometrics. Also instructors can use the book as a textbook or supplementary reading material for graduate courses on biometric recognition, human perception, computer vision, or other relevant seminars.
650		0	_aCOMPUTER SCIENCE.
650		0	_aDATA STRUCTURES (COMPUTER SCIENCE).
650		0	_aDATA ENCRYPTION (COMPUTER SCIENCE).
650		0	_aMULTIMEDIA SYSTEMS.
650		0	_aCOMPUTER VISION.
650		0	_aOPTICAL PATTERN RECOGNITION.
650	1	4	_aCOMPUTER SCIENCE.
650	2	4	_aPATTERN RECOGNITION.
650	2	4	_aIMAGE PROCESSING AND COMPUTER VISION.
650	2	4	_aDATA ENCRYPTION.
650	2	4	_aDATA STRUCTURES, CRYPTOLOGY AND INFORMATION THEORY.
650	2	4	_aUSER INTERFACES AND HUMAN COMPUTER INTERACTION.
650	2	4	_aMULTIMEDIA INFORMATION SYSTEMS.
700	1		_aChellappa, Rama. _eauthor.
700	1		_aZhao, Wenyi. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387264073
830		0	_aInternational Series on Biometrics ; _v5
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-29486-5 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SCS
942			_2ddc _cER
999			_c56964 _d56964