LEADER 03798nam 22005895 450 001 9910409678603321 005 20200629122715.0 010 $a981-15-3883-2 024 7 $a10.1007/978-981-15-3883-4 035 $a(CKB)4100000010770762 035 $a(DE-He213)978-981-15-3883-4 035 $a(MiAaPQ)EBC6145305 035 $a(PPN)243224109 035 $a(EXLCZ)994100000010770762 100 $a20200326d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHuman Emotion Recognition from Face Images /$fby Paramartha Dutta, Asit Barman 205 $a1st ed. 2020. 210 1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2020. 215 $a1 online resource (XIX, 264 p. 112 illus., 99 illus. in color.) 225 1 $aCognitive Intelligence and Robotics,$x2520-1956 311 $a981-15-3882-4 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- Distance Signature for Recognizing Human Emotions -- Shape Signature for recognizing Human Emotion -- Distance Shape Signature Duo Ford Determination of Human Emotion -- Distance Texture Signature Duo for Determination of Human Emotion. 330 $aThis book discusses human emotion recognition from face images using different modalities, highlighting key topics in facial expression recognition, such as the grid formation, distance signature, shape signature, texture signature, feature selection, classifier design, and the combination of signatures to improve emotion recognition. The book explains how six basic human emotions can be recognized in various face images of the same person, as well as those available from benchmark face image databases like CK+, JAFFE, MMI, and MUG. The authors present the concept of signatures for different characteristics such as distance and shape texture, and describe the use of associated stability indices as features, supplementing the feature set with statistical parameters such as range, skewedness, kurtosis, and entropy. In addition, they demonstrate that experiments with such feature choices offer impressive results, and that performance can be further improved by combining the signatures rather than using them individually. There is an increasing demand for emotion recognition in diverse fields, including psychotherapy, biomedicine, and security in government, public and private agencies. This book offers a valuable resource for researchers working in these areas. 410 0$aCognitive Intelligence and Robotics,$x2520-1956 606 $aUser interfaces (Computer systems) 606 $aOptical data processing 606 $aPattern perception 606 $aUser Interfaces and Human Computer Interaction$3https://scigraph.springernature.com/ontologies/product-market-codes/I18067 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 615 0$aUser interfaces (Computer systems) 615 0$aOptical data processing. 615 0$aPattern perception. 615 14$aUser Interfaces and Human Computer Interaction. 615 24$aImage Processing and Computer Vision. 615 24$aPattern Recognition. 676 $a006.37 700 $aDutta$b Paramartha$4aut$4http://id.loc.gov/vocabulary/relators/aut$0852950 702 $aBarman$b Asit$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910409678603321 996 $aHuman Emotion Recognition from Face Images$91947572 997 $aUNINA