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ECCV
2006
Springer

Real-Time Upper Body Detection and 3D Pose Estimation in Monoscopic Images

10 years 4 months ago
Real-Time Upper Body Detection and 3D Pose Estimation in Monoscopic Images
This paper presents a novel solution to the difficult task of both detecting and estimating the 3D pose of humans in monoscopic images. The approach consists of two parts. Firstly the location of a human is identified by a probabalistic assembly of detected body parts. Detectors for the face, torso and hands are learnt using adaBoost. A pose likliehood is then obtained using an a priori mixture model on body configuration and possible configurations assembled from available evidence using RANSAC. Once a human has been detected, the location is used to initialise a matching algorithm which matches the silhouette and edge map of a subject with a 3D model. This is done efficiently using chamfer matching, integral images and pose estimation from the initial detection stage. We demonstrate the application of the approach to large, cluttered natural images and at near framerate operation (16fps) on lower resolution video streams.
Antonio S. Micilotta, Eng-Jon Ong, Richard Bowden
Added 16 Oct 2009
Updated 16 Oct 2009
Type Conference
Year 2006
Where ECCV
Authors Antonio S. Micilotta, Eng-Jon Ong, Richard Bowden
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