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Titlebook: Human Action Recognition with Depth Cameras; Jiang Wang,Zicheng Liu,Ying Wu Book 2014 The Author(s) 2014 3D Action Recognition.3D Sensors.

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发表于 2025-3-21 19:04:40 | 显示全部楼层 |阅读模式
书目名称Human Action Recognition with Depth Cameras
编辑Jiang Wang,Zicheng Liu,Ying Wu
视频video
概述Presents a comprehensive overview of the state of the art in feature representation and machine learning algorithms for action recognition from depth sensors.Provides in-depth descriptions of novel fe
丛书名称SpringerBriefs in Computer Science
图书封面Titlebook: Human Action Recognition with Depth Cameras;  Jiang Wang,Zicheng Liu,Ying Wu Book 2014 The Author(s) 2014 3D Action Recognition.3D Sensors.
描述Action recognition technology has many real-world applications in human-computer interaction, surveillance, video retrieval, retirement home monitoring, and robotics. The commoditization of depth sensors has also opened up further applications that were not feasible before. This text focuses on feature representation and machine learning algorithms for action recognition from depth sensors. After presenting a comprehensive overview of the state of the art, the authors then provide in-depth descriptions of their recently developed feature representations and machine learning techniques, including lower-level depth and skeleton features, higher-level representations to model the temporal structure and human-object interactions, and feature selection techniques for occlusion handling. This work enables the reader to quickly familiarize themselves with the latest research, and to gain a deeper understanding of recently developed techniques. It will be of great use for both researchers andpractitioners.
出版日期Book 2014
关键词3D Action Recognition; 3D Sensors; Actionlet Ensemble; Depth Cameras; Human Action/Activity Recognition;
版次1
doihttps://doi.org/10.1007/978-3-319-04561-0
isbn_softcover978-3-319-04560-3
isbn_ebook978-3-319-04561-0Series ISSN 2191-5768 Series E-ISSN 2191-5776
issn_series 2191-5768
copyrightThe Author(s) 2014
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发表于 2025-3-22 00:12:37 | 显示全部楼层
Introduction,Recent years have witnessed great progress in depth sensor technology, which brings huge opportunities for action recognition field. This chapter gives an overview of the recent development of the 3D action recognition approaches, and presents the motivations of the 3D action recognition features, models, and representations in this book.
发表于 2025-3-22 03:20:31 | 显示全部楼层
Conclusion,This chapter concludes the methods that we introduce in this book, and presents the current challenges and further directions in 3D action recognition using depth cameras.
发表于 2025-3-22 07:44:11 | 显示全部楼层
Jiang Wang,Zicheng Liu,Ying WuPresents a comprehensive overview of the state of the art in feature representation and machine learning algorithms for action recognition from depth sensors.Provides in-depth descriptions of novel fe
发表于 2025-3-22 09:33:31 | 显示全部楼层
SpringerBriefs in Computer Sciencehttp://image.papertrans.cn/h/image/428921.jpg
发表于 2025-3-22 14:58:59 | 显示全部楼层
https://doi.org/10.1007/978-3-319-04561-03D Action Recognition; 3D Sensors; Actionlet Ensemble; Depth Cameras; Human Action/Activity Recognition;
发表于 2025-3-22 20:16:51 | 显示全部楼层
Learning Actionlet Ensemble for 3D Human Action Recognition,gh intra-class variations and complicated temporal structures. The recently developed commodity depth sensors open up new possibilities of dealing with this problem by providing 3D depth data of the scene. This information not only facilitates a rather powerful human motion capturing technique, but
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