02910nam 22006015 450 991025481380332120200702153120.03-319-57021-810.1007/978-3-319-57021-1(CKB)4340000000062228(DE-He213)978-3-319-57021-1(MiAaPQ)EBC4920975(PPN)203671074(EXLCZ)99434000000006222820170719d2017 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierGesture Recognition /edited by Sergio Escalera, Isabelle Guyon, Vassilis Athitsos1st ed. 2017.Cham :Springer International Publishing :Imprint: Springer,2017.1 online resource (XII, 578 p. 214 illus., 170 illus. in color.) The Springer Series on Challenges in Machine Learning,2520-131X3-319-57020-X Includes bibliographical references at the end of each chapters.Preface -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5.This book presents a selection of chapters, written by leading international researchers, related to the automatic analysis of gestures from still images and multi-modal RGB-Depth image sequences. It offers a comprehensive review of vision-based approaches for supervised gesture recognition methods that have been validated by various challenges. Several aspects of gesture recognition are reviewed, including data acquisition from different sources, feature extraction, learning, and recognition of gestures.The Springer Series on Challenges in Machine Learning,2520-131XArtificial intelligenceOptical data processingPattern recognitionArtificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Image Processing and Computer Visionhttps://scigraph.springernature.com/ontologies/product-market-codes/I22021Pattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XArtificial intelligence.Optical data processing.Pattern recognition.Artificial Intelligence.Image Processing and Computer Vision.Pattern Recognition.006.4Escalera Sergioedthttp://id.loc.gov/vocabulary/relators/edtGuyon Isabelleedthttp://id.loc.gov/vocabulary/relators/edtAthitsos Vassilisedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910254813803321Gesture Recognition2517168UNINA