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010   $a3-319-62212-9
024 7 $a10.1007/978-3-319-62212-5
035   $a(CKB)4340000000062808
035   $a(DE-He213)978-3-319-62212-5
035   $a(MiAaPQ)EBC6295742
035   $a(MiAaPQ)EBC5610913
035   $a(Au-PeEL)EBL5610913
035   $a(OCoLC)1079007551
035   $a(PPN)203669053
035   $a(EXLCZ)994340000000062808
100   $a20170705d2018      u|         0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aGesture Recognition $ePrinciples, Techniques and Applications /$fby Amit Konar, Sriparna Saha
205   $a1st ed. 2018.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018.
215   $a1 online resource (XVIII, 276 p. 99 illus., 73 illus. in color.)
225 1 $aStudies in Computational Intelligence,$x1860-949X ;$v724
311   $a3-319-62210-2 
327   $aIntroduction -- Radon Transform based Automatic Posture Recognition in Ballet Dance -- Fuzzy Image Matching Based Posture Recognition in Ballet Dance -- Gesture Driven Fuzzy Interface System For Car Racing Game -- Type-2 Fuzzy Classifier based Pathological Disorder Recognition -- Probabilistic Neural Network based Dance Gesture Recognition -- Differential Evolution based Dance Composition -- EEG-Gesture based Artificial Limb Movement for Rehabilitative Applications -- Conclusions and Future Directions -- Index.
330   $aThis book presents a thorough analysis of gestural data extracted from raw images and/or range data with an aim to recognize the gestures conveyed by the data. It covers image morphological analysis, type-2 fuzzy logic, neural networks and evolutionary computation for classification of gestural data. The application areas include the recognition of primitive postures in ballet/classical Indian dances, detection of pathological disorders from gestural data of elderly people, controlling motion of cars in gesture-driven gaming and gesture-commanded robot control for people with neuro-motor disability. The book is unique in terms of its content, originality and lucid writing style. Primarily intended for graduate students and researchers in the field of electrical/computer engineering, the book will prove equally useful to computer hobbyists and professionals engaged in building firmware for human-computer interfaces. A prerequisite of high school level mathematics is sufficient to understand most of the chapters in the book. A basic background in image processing, although not mandatory, would be an added advantage for certain sections.
410  0$aStudies in Computational Intelligence,$x1860-949X ;$v724
606   $aComputational intelligence
606   $aArtificial intelligence
606   $aUser interfaces (Computer systems)
606   $aPattern recognition
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aUser Interfaces and Human Computer Interaction$3https://scigraph.springernature.com/ontologies/product-market-codes/I18067
606   $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X
615  0$aComputational intelligence.
615  0$aArtificial intelligence.
615  0$aUser interfaces (Computer systems).
615  0$aPattern recognition.
615 14$aComputational Intelligence.
615 24$aArtificial Intelligence.
615 24$aUser Interfaces and Human Computer Interaction.
615 24$aPattern Recognition.
676   $a006.4
700   $aKonar$b Amit$4aut$4http://id.loc.gov/vocabulary/relators/aut$0542703
702   $aSaha$b Sriparna$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
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906   $aBOOK
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996   $aGesture Recognition$92535453
997   $aUNINA