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008			160204s2016 gw | s |||| 0|eng d
020			_a9783319290881
040			_aES-MaUEC
050		4	_aQ325.5 _bM376 2016
082	0	4	_a621.382
100	1		_aMason, James Eric _0Local _998577
245	1	0	_aMachine Learning Techniques for Gait Biometric Recognition : _bUsing the Ground Reaction Force _cby James Eric Mason, Issa Traoré, Isaac Woungang
250			_a1st ed.
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XXXIV, 223 páginas) _b76 ilustraciones, 73 ilustraciones en color
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
505	0		_aIntroduction -- Background -- Experimental Design and Dataset -- Feature Extraction.-Normalization -- Classification -- Measured Performance -- Experimental Analysis -- Conclusion.
520	3		_aThis book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition · provides detailed discussions of key research challenges and open research issues in gait biometrics recognition · compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear.
650	0	7	_aBiometría _2embne _9139105
650	0	7	_aSeguridad informática _9158200 _2embne
700	1		_aTraoré, Issa _0Local _998578
700	1		_aWoungang, Isaac _0Local _998579
710	2		_aSpringerLink (Online service) _0Local _9106996
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-29088-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319290881
907			_a.b12948147 _b10-10-17 _c21-11-16
942			_2lcc _cLE
945			_aQ325.5 M376 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11591614 _z06-04-17
988			_aEBOOK, asignarmaterias , EBSPRINGER
998			_am _a_alco _a_vill _b - - _cm _dz _e- _feng _ggw _h0