Human Activity Recognition and Prediction (Hardcover, 1st ed. 2016)

This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	December 2015
First published:	2016
Editors:	Yun Fu
Dimensions:	235 x 155 x 13mm (L x W x T)
Format:	Hardcover
Pages:	174
Edition:	1st ed. 2016
ISBN-13:	978-3-319-27002-9
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Books > Computing & IT > Applications of computing > Image processing > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	3-319-27002-8
Barcode:	9783319270029

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