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001 978-3-319-11325-8
003 DE-He213
005 20200421112046.0
007 cr nn 008mamaa
008 141113s2015 gw | s |||| 0|eng d
020 _a9783319113258
_9978-3-319-11325-8
024 7 _a10.1007/978-3-319-11325-8
_2doi
050 4 _aTJ210.2-211.495
050 4 _aT59.5
072 7 _aTJFM1
_2bicssc
072 7 _aTEC037000
_2bisacsh
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.892
_223
100 1 _aSpehr, Jens.
_eauthor.
245 1 0 _aOn Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities
_h[electronic resource] /
_cby Jens Spehr.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXV, 199 p. 107 illus., 92 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 _aStudies in Systems, Decision and Control,
_x2198-4182 ;
_v11
505 0 _aIntroduction -- Probabilistic Graphical Models -- Hierarchical Graphical Models -- Learning of Hierarchical Models.-Object Recognition -- Human Pose Estimation -- Scene Understanding for Intelligent Vehicles -- Conclusion.
520 _aIn many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model the environment of the vehicle for an efficient and robust interpretation of the scene in real-time.
650 0 _aEngineering.
650 0 _aImage processing.
650 0 _aPattern recognition.
650 0 _aComputational intelligence.
650 0 _aRobotics.
650 0 _aAutomation.
650 1 4 _aEngineering.
650 2 4 _aRobotics and Automation.
650 2 4 _aComputational Intelligence.
650 2 4 _aImage Processing and Computer Vision.
650 2 4 _aPattern Recognition.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319113241
830 0 _aStudies in Systems, Decision and Control,
_x2198-4182 ;
_v11
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-11325-8
912 _aZDB-2-ENG
942 _cEBK
999 _c56928
_d56928