Gesture Recognition
Editors: Escalera, Sergio, Guyon, Isabelle, Athitsos, Vassilis (Eds.)
Free Preview- Gives readers a comprehensive analysis on gesture recognition, defining a new taxonomy for the field
- Focusses on supervised machine learning methods for gesture recognition
- Presents an open-source C++ library for real-time gesture recognition
- Reviews recent research involving deep learning architectures in order to deal with gesture and action recognition problems
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- About this book
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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.
- Table of contents (19 chapters)
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Challenges in Multi-modal Gesture Recognition
Pages 1-60
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Human Gesture Recognition on Product Manifolds
Pages 61-87
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Sign Language Recognition Using Sub-units
Pages 89-118
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MAGIC Summoning: Towards Automatic Suggesting and Testing of Gestures with Low Probability of False Positives During Use
Pages 119-154
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Language-Motivated Approaches to Action Recognition
Pages 155-181
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Table of contents (19 chapters)
- Download Preface 1 PDF (51.1 KB)
- Download Sample pages 2 PDF (1,003.4 KB)
- Download Table of contents PDF (71.2 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Gesture Recognition
- Editors
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- Sergio Escalera
- Isabelle Guyon
- Vassilis Athitsos
- Series Title
- The Springer Series on Challenges in Machine Learning
- Copyright
- 2017
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG
- eBook ISBN
- 978-3-319-57021-1
- DOI
- 10.1007/978-3-319-57021-1
- Hardcover ISBN
- 978-3-319-57020-4
- Softcover ISBN
- 978-3-319-86059-6
- Series ISSN
- 2520-131X
- Edition Number
- 1
- Number of Pages
- XII, 578
- Number of Illustrations
- 44 b/w illustrations, 170 illustrations in colour
- Topics
