Obdržálek Stěpán, Kurillo Gregorij, Han Jay, Abresch Ted, Bajcsy Ruzena
University of California, Berkeley, USA.
Stud Health Technol Inform. 2012;173:320-4.
We present a real-time algorithm for human pose detection and tracking from vision-based 3D data and its application to tele-rehabilitation in virtual environments. We employ stereo camera(s) to capture 3D avatars of geographically dislocated patient and therapist in real-time, while sending the data remotely and displaying it in a virtual scene. A pose detection and tracking algorithm extracts kinematic parameters from each participant and determines pose similarity. The pose similarity score is used to quantify patient's performance and provide real-time feedback for remote rehabilitation.
我们提出了一种用于从基于视觉的3D数据中进行人体姿态检测和跟踪的实时算法及其在虚拟环境中的远程康复应用。我们使用立体相机实时捕捉地理位置分散的患者和治疗师的3D虚拟形象，同时远程发送数据并在虚拟场景中显示。一种姿态检测和跟踪算法从每个参与者中提取运动学参数并确定姿态相似度。姿态相似度得分用于量化患者的表现并为远程康复提供实时反馈。
