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Gesture Recognition: Principles, Techniques and Applications (Studies in Computational Intelligence, 724, Band 724) - Hardcover

Buch 236 von 538: Studies in Computational Intelligence

Konar, Amit; Saha, Sriparna

 
9783319622101: Gesture Recognition: Principles, Techniques and Applications (Studies in Computational Intelligence, 724, Band 724)

Inhaltsangabe

This 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 issufficient 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.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

Dr. Pratyusha Rakshit received her B.Tech. degree in Electronics and Communication Engineering (ECE) from the Institute of Engineering and Management, Kolkata, India, and her M.E. degree in Control Engineering from the Department of Electronics and Telecommunication Engineering (ETCE), Jadavpur University, Kolkata, India in 2010 and 2012, respectively. She was awarded her Ph.D. (Engineering) degree from Jadavpur University, India, in 2016 and is currently an Assistant Professor at its ETCE Department. She was awarded Gold Medals for securing the highest marks in B.Tech. in ECE and among all the courses of M.E. respectively in 2010 and 2012. She was the recipient of the CSIR Senior Research Fellowship, INSPIRE Fellowship and UGC UPE-II Junior Research Fellowship. Her principal research interests include artificial and computational intelligence, evolutionary computation, robotics, bioinformatics, pattern recognition, fuzzy logic, cognitive science and human-computer interaction. She is the author of over 50 papers published in top international journals and conference proceedings. She also serves as a reviewer for IEEE-TFS, IEEE-SMC: Systems, Neurocomputing, Information Sciences, and Applied Soft Computing. Dr. Amit Konar is currently a Professor at the Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India. Dr. Konar is the author of over 350 publications, including books/monographs, peer-reviewed book chapters and papers, all with leading international publishers. He is an Associate Editor of several prestigious journals, including IEEE Transactions, Elsevier, Springer and IOS Press, the Netherlands. He has undertaken several prestigious research projects, including UGC's departmental research support (DRS) scheme, DIT's national project on Perception Engineering and UGC's excellence program in Cognitive Science. Dr. Konar was a recipient of the AICTE-accredited 1997-2000 Career Award for young teachers. He has been nominated as a Fellow of the National Academy of Engineering, and his current research interests include human-computer interfacing, cognitive neuroscience, robotics and machine intelligence.

Von der hinteren Coverseite

This 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.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.