找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

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

[復制鏈接]
查看: 36065|回復: 35
樓主
發(fā)表于 2025-3-21 19:04:40 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Human Action Recognition with Depth Cameras
編輯Jiang Wang,Zicheng Liu,Ying Wu
視頻videohttp://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
關鍵詞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
The information of publication is updating

書目名稱Human Action Recognition with Depth Cameras影響因子(影響力)




書目名稱Human Action Recognition with Depth Cameras影響因子(影響力)學科排名




書目名稱Human Action Recognition with Depth Cameras網絡公開度




書目名稱Human Action Recognition with Depth Cameras網絡公開度學科排名




書目名稱Human Action Recognition with Depth Cameras被引頻次




書目名稱Human Action Recognition with Depth Cameras被引頻次學科排名




書目名稱Human Action Recognition with Depth Cameras年度引用




書目名稱Human Action Recognition with Depth Cameras年度引用學科排名




書目名稱Human Action Recognition with Depth Cameras讀者反饋




書目名稱Human Action Recognition with Depth Cameras讀者反饋學科排名




單選投票, 共有 1 人參與投票
 

0票 0.00%

Perfect with Aesthetics

 

1票 100.00%

Better Implies Difficulty

 

0票 0.00%

Good and Satisfactory

 

0票 0.00%

Adverse Performance

 

0票 0.00%

Disdainful Garbage

您所在的用戶組沒有投票權限
沙發(fā)
發(fā)表于 2025-3-22 00:12:37 | 只看該作者
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.
板凳
發(fā)表于 2025-3-22 03:20:31 | 只看該作者
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.
地板
發(fā)表于 2025-3-22 07:44:11 | 只看該作者
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
5#
發(fā)表于 2025-3-22 09:33:31 | 只看該作者
SpringerBriefs in Computer Sciencehttp://image.papertrans.cn/h/image/428921.jpg
6#
發(fā)表于 2025-3-22 14:58:59 | 只看該作者
https://doi.org/10.1007/978-3-319-04561-03D Action Recognition; 3D Sensors; Actionlet Ensemble; Depth Cameras; Human Action/Activity Recognition;
7#
發(fā)表于 2025-3-22 20:16:51 | 只看該作者
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
8#
發(fā)表于 2025-3-22 22:27:45 | 只看該作者
9#
發(fā)表于 2025-3-23 02:43:51 | 只看該作者
10#
發(fā)表于 2025-3-23 08:20:00 | 只看該作者
 關于派博傳思  派博傳思旗下網站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網 吾愛論文網 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經驗總結 SCIENCEGARD IMPACTFACTOR 派博系數 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網安備110108008328) GMT+8, 2025-10-14 06:03
Copyright © 2001-2015 派博傳思   京公網安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
嘉定区| 泰来县| 旬阳县| 屏东市| 内黄县| 米脂县| 湖北省| 正镶白旗| 阳高县| 洪洞县| 武汉市| 宾川县| 四平市| 徐汇区| 泸溪县| 昭觉县| 出国| 台北市| 哈尔滨市| 金寨县| 滨州市| 隆子县| 和政县| 宽城| 古丈县| 绍兴市| 凭祥市| 伊川县| 思南县| 巴中市| 扎兰屯市| 洛隆县| 高唐县| 商南县| 宁化县| 广宗县| 波密县| 赣州市| 岚皋县| 吉林省| 东方市|