Real-time upper body detection and 3D pose estimation in monoscopic images
Micilotta, AS, Ong, EJ and Bowden, R (2006) Real-time upper body detection and 3D pose estimation in monoscopic images In: ECCV 2006, 2006-05-07 - 2006-05-13, Graz, Austria.
MicilottaOngBowdenECCV06.pdf - Accepted version Manuscript
Available under License : See the attached licence file.
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.
|Item Type:||Conference or Workshop Item (Conference Paper)|
|Divisions :||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing|
|Identification Number :||https://doi.org/10.1007/11744078_11|
|Additional Information :||The original publication is available at http://www.springerlink.com/|
|Depositing User :||Symplectic Elements|
|Date Deposited :||21 May 2012 15:15|
|Last Modified :||09 Jun 2014 13:18|
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