Gesture Recognition, 1st ed. 2017 The Springer Series on Challenges in Machine Learning Series
Coordonnateurs : Escalera Sergio, Guyon Isabelle, Athitsos Vassilis
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.
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
Includes supplementary material: sn.pub/extras
Includes supplementary material: sn.pub/extras
Date de parution : 08-2018
Ouvrage de 578 p.
15.5x23.5 cm
Date de parution : 07-2017
Ouvrage de 578 p.
15.5x23.5 cm