| 書目名稱 | Human Action Recognition with Depth Cameras |
| 編輯 | Jiang Wang,Zicheng Liu,Ying Wu |
| 視頻video | http://file.papertrans.cn/429/428921/428921.mp4 |
| 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 |
| 叢書名稱 | SpringerBriefs in Computer Science |
| 圖書封面 |  |
| 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 |
| 關(guān)鍵詞 | 3D Action Recognition; 3D Sensors; Actionlet Ensemble; Depth Cameras; Human Action/Activity Recognition; |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-04561-0 |
| isbn_softcover | 978-3-319-04560-3 |
| isbn_ebook | 978-3-319-04561-0Series ISSN 2191-5768 Series E-ISSN 2191-5776 |
| issn_series | 2191-5768 |
| copyright | The Author(s) 2014 |
|Archiver|手機(jī)版|小黑屋|
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