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標題Title: Human skeleton tracking from depth data using geodesic distances and optical flow
作者Authors: 徐苡庭,巫佳哲..等
上傳單位Department: 資訊工程系
上傳時間Date: 2013-12-30
上傳者Author: 徐苡庭
審核單位Department: 資訊工程系
審核老師Teacher: 李南逸
檔案類型Categories: 課堂報告In-class Report
關鍵詞Keyword: Keywords: Human pose estimation Depth imaging Geodesic distances
摘要Abstract: In this paper, we present a method for human full-body pose estimation from depth data that can be obtained
using Time of Flight (ToF) cameras or the Kinect device. Our approach consists of robustly detecting anatomical
landmarks in the 3D data and fitting a skeleton body model using constrained inverse kinematics. Instead of
relying on appearance-based features for interest point detection that can vary strongly with illumination and
pose changes, we build upon a graph-based representation of the depth data that allows us tomeasure geodesic
distances between body parts. As these distances do not change with body movement, we are able to localize
anatomical landmarks independent of pose. For differentiation of body parts that occlude each other,we employ
motion information, obtained from the optical flow between subsequent intensity images. We provide a
qualitative and quantitative evaluation of our pose tracking method on ToF and Kinect sequences containing
movements of varying complexity.

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2013_12_f9697b5f.pptx 1796Kb pptx 75 78
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