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001 978-3-319-24865-3
003 DE-He213
005 20200421112547.0
007 cr nn 008mamaa
008 151022s2015 gw | s |||| 0|eng d
020 _a9783319248653
_9978-3-319-24865-3
024 7 _a10.1007/978-3-319-24865-3
_2doi
050 4 _aQH323.5
072 7 _aUYQP
_2bicssc
072 7 _aUYQV
_2bicssc
072 7 _aCOM016000
_2bisacsh
082 0 4 _a570.15195
_223
245 1 0 _aAdaptive Biometric Systems
_h[electronic resource] :
_bRecent Advances and Challenges /
_cedited by Ajita Rattani, Fabio Roli, Eric Granger.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aX, 134 p. 44 illus., 24 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Computer Vision and Pattern Recognition,
_x2191-6586
520 _aThis timely and interdisciplinary volume presents a detailed overview of the latest advances and challenges remaining in the field of adaptive biometric systems. A broad range of techniques are provided from an international selection of pre-eminent authorities, collected together under a unified taxonomy and designed to be applicable to any pattern recognition system. Topics and features: Presents a thorough introduction to the concept of adaptive biometric systems, detailing their taxonomy, levels of adaptation, and open issues and challenges Reviews systems for adaptive face recognition that perform self-updating of facial models using operational (unlabeled) data Describes a novel semi-supervised training strategy known as fusion-based co-training Examines the characterization and recognition of human gestures in videos Discusses a selection of learning techniques that can be applied to build an adaptive biometric system Investigates procedures for handling temporal variance in facial biometrics due to aging Proposes a score-level fusion scheme for an adaptive multimodal biometric system This comprehensive text/reference will be of great interest to researchers and practitioners engaged in systems science, information security or biometrics. Postgraduate and final-year undergraduate students of computer engineering will also appreciate the coverage of intelligent and adaptive schemes for cutting-edge pattern recognition and signal processing in changing environments.
650 0 _aComputer science.
650 0 _aArtificial intelligence.
650 0 _aPattern recognition.
650 0 _aBiometrics (Biology).
650 1 4 _aComputer Science.
650 2 4 _aBiometrics.
650 2 4 _aPattern Recognition.
650 2 4 _aSignal, Image and Speech Processing.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aRattani, Ajita.
_eeditor.
700 1 _aRoli, Fabio.
_eeditor.
700 1 _aGranger, Eric.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319248639
830 0 _aAdvances in Computer Vision and Pattern Recognition,
_x2191-6586
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-24865-3
912 _aZDB-2-SCS
942 _cEBK
999 _c58659
_d58659