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010   $a3-319-27004-4
024 7 $a10.1007/978-3-319-27004-3
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035   $a(EBL)4205835
035   $a(SSID)ssj0001597275
035   $a(PQKBManifestationID)16296544
035   $a(PQKBTitleCode)TC0001597275
035   $a(PQKBWorkID)14885985
035   $a(PQKB)10621480
035   $a(DE-He213)978-3-319-27004-3
035   $a(MiAaPQ)EBC4205835
035   $z(PPN)258870516
035   $a(PPN)190882069
035   $a(EXLCZ)993780000000094088
100   $a20151223d2016      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aHuman Activity Recognition and Prediction /$fedited by Yun Fu
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (179 p.)
300   $aDescription based upon print version of record.
311   $a3-319-27002-8 
320   $aIncludes bibliographical references at the end of each chapters.
327   $aIntroduction -- Action and Activities -- Action Recognition and Human Interaction -- Multimodal Action Recognition -- RGB-D Action Recognition -- Actionlets and Activity Prediction -- Time Series Modeling for Activity Prediction -- RGB-D Action Prediction.
330   $aThis book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques. .
606   $aSignal processing
606   $aImage processing
606   $aSpeech processing systems
606   $aOptical data processing
606   $aBiometrics (Biology)
606   $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051
606   $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021
606   $aBiometrics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22040
615  0$aSignal processing.
615  0$aImage processing.
615  0$aSpeech processing systems.
615  0$aOptical data processing.
615  0$aBiometrics (Biology).
615 14$aSignal, Image and Speech Processing.
615 24$aImage Processing and Computer Vision.
615 24$aBiometrics.
676   $a620
702   $aFu$b Yun$4edt$4http://id.loc.gov/vocabulary/relators/edt
906   $aBOOK
912   $a9910254204703321
996   $aHuman Activity Recognition and Prediction$91545085
997   $aUNINA