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001			96010
003			ES-MaUEC
005			20230102112733.0
006			m o d
007			cr cnu|||unuuu
008			170518s2017 gw a ob 001 0 eng d
020			_a3662536900
020			_a3662536927 _q(electronic bk.)
020			_a9783662536902
020			_a9783662536926 _q(electronic bk.)
020			_z9783662536902 _q(print)
040			_aGW5XE _cGW5XE _dYDX _dOCLCF _dUAB _dESU _dAZU _dUPM _dIOG _dCOO _dMERER _dVT2 _dOCLCQ _dU3W _dES-MaUEC _bspa
050		4	_aTK7882.P7 _b2017 EB
245	0	0	_aHuman motion sensing and recognition : _ba fuzzy qualitative approach _cHonghai Liu, Zhaojie Ju, Xiaofei Ji, Chee Seng Chan, Mehdi Khoury.
264		1	_aBerlin, Germany _bSpringer _c2017.
300			_a1 recurso en línea (xvi, 281 páginas) _bilustraciones (algunas a color)
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF
490	0		_aStudies in computational intelligence _x1860-949X _vvolume 675
500			_aSpringerLink _bSpringer Engineering eBooks 2017 English+International
504			_aIncluye referencias bibliográficas e índice
505	0		_aIntroduction -- Fuzzy Qualitative Trigonometry -- Fuzzy Qualitative Robot Kinematics -- Fuzzy Qualitative Human Motion Analysis -- Fuzzy Gaussian Mixture Models -- Fuzzy Empirical Copula for Estimating Data Dependence Structure -- A Unified Fuzzy Framework for Human Hand Motion Recognition -- Human Hand Motion Analysis with Multisensory Information -- A Novel Approach to Extract Hand Gesture Feature in Depth Images -- Recognizing Constrained 3D Human Motion: An Inference Approach -- Study of Human Action Recognition Based on Improved Spatio-temporal Features -- A View-invariant Action Recognition based on Multi-view Space Hidden Markov Models.
520	3		_aThis book introduces readers to the latest exciting advances in human motion sensing and recognition, from the theoretical development of fuzzy approaches to their applications. The topics covered include human motion recognition in 2D and 3D, hand motion analysis with contact sensors, and vision-based view-invariant motion recognition, especially from the perspective of Fuzzy Qualitative techniques. With the rapid development of technologies in microelectronics, computers, networks, and robotics over the last decade, increasing attention has been focused on human motion sensing and recognition in many emerging and active disciplines where human motions need to be automatically tracked, analyzed or understood, such as smart surveillance, intelligent human-computer interaction, robot motion learning, and interactive gaming. Current challenges mainly stem from the dynamic environment, data multi-modality, uncertain sensory information, and real-time issues. These techniques are shown to effectively address the above challenges by bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in intelligent systems. The book not only serves as a valuable reference source for researchers and professionals in the fields of computer vision and robotics, but will also benefit practitioners and graduates/postgraduates seeking advanced information on fuzzy techniques and their applications in motion analysis.
650		7	_aSistemas difusos _2embne _0(OCoLC)fst00936814 _0 _9152595
700	1		_aChan, Chee Seng, _eautor
700	1		_aJi, Xiaofei, _eautor
700	1		_aJu, Zhaojie, _eautor
700	1		_aKhoury, Mehdi, _eautor
700	1		_aLiu, Honghai _c(Professor of Intelligent Systems), _eautor
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-3-662-53692-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
988			_aEBOOK, asignarmaterias, EBSPRINGER_2017D
998			_b02/2018 _dz _e- _zSI
999			_c96010 _d96010 _x1