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008 150903s2013 xxk| o |||| 0|eng d
020 _a9781447147305
_99781447147305
024 7 _a10.1007/9781447147305
_2doi
035 _avtls000339901
039 9 _a201509030320
_bVLOAD
_c201404300406
_dVLOAD
_y201402061012
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQ337.5
100 1 _aAhad, Md. Atiqur Rahman.
_eautor
_9315173
245 1 0 _aMotion History Images for Action Recognition and Understanding /
_cby Md. Atiqur Rahman Ahad.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2013.
300 _axvI, 116 páginas 34 ilustraciones
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aSpringerBriefs in Computer Science,
_x2191-5768
500 _aSpringer eBooks
505 0 _aIntroduction -- Action Representation -- Motion History Image -- Action Datasets and MHI.
520 _aHuman action analysis and recognition is a relatively mature field, yet one which is often not well understood by students and researchers.  The large number of possible variations in human motion and appearance, camera viewpoint, and environment, present considerable challenges.  Some important and common problems remain unsolved by the computer vision community. However, many valuable approaches have been proposed over the past decade, including the motion history image (MHI) method. This method has received significant attention, as it offers greater robustness and performance than other techniques. This work presents a comprehensive review of these state-of-the-art approaches and their applications, with a particular focus on the MHI method and its variants.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9781447147299
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4471-4730-5
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c286513
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