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A Survey on Human Motion Analysis from Depth Data

机译:基于深度数据的人体运动分析研究

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摘要

Human pose estimation has been actively studied for decades. While traditional approaches rely on 2d data like images or videos, the development of Time-of-Flight cameras and other depth sensors created new opportunities to advance the field. We give an overview of recent approaches that perform human motion analysis which includes depth-based and skeleton-based activity recognition, head pose estimation, facial feature detection, facial performance capture, hand pose estimation and hand gesture recognition. While the focus is on approaches using depth data, we also discuss traditional image based methods to provide a broad overview of recent developments in these areas.
机译:人体姿势估计已被积极研究了数十年。尽管传统方法依赖于2D数据(例如图像或视频),但飞行时间相机和其他深度传感器的发展为推动该领域的发展创造了新机遇。我们概述了执行人体运动分析的最新方法,包括基于深度和基于骨骼的活动识别,头部姿势估计,面部特征检测,面部表情捕获,手势估计和手势识别。虽然重点放在使用深度数据的方法上,但我们还将讨论基于传统图像的方法,以提供有关这些领域最新进展的广泛概述。

著录项

  • 来源
  • 会议地点 Saarbrucken(DE);Dagstuhl(DE)
  • 作者单位

    University of Kentucky, 329 Rose St., Lexington, KY. 40508, U.S.A.;

    University of Kentucky, 329 Rose St., Lexington, KY, 40508, U.S.A.;

    Microsoft, One Microsoft Way, Redmond, WA, 980, 52, U.S.A.;

    SRI International Sarnoff, 201 Washington Rd, Princeton, N.I, 08540, U.S.A.;

    University of Kentucky, 329 Rose St., Lexington, KY, 40508, U.S.A.;

    University of Bonn, Roemerstrasse 164, 53117 Bonn, Germany;

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  • 原文格式 PDF
  • 正文语种 eng
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