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Efficient Estimation of Human Upper Body Pose in Static Depth Images

Holt, B and Bowden, R (2013) Efficient Estimation of Human Upper Body Pose in Static Depth Images Communications in Computer and Information Science, 359 CC. pp. 399-410.

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Abstract

Automatic estimation of human pose has long been a goal of computer vision, to which a solution would have a wide range of applications. In this paper we formulate the pose estimation task within a regression and Hough voting framework to predict 2D joint locations from depth data captured by a consumer depth camera. In our approach the offset from each pixel to the location of each joint is predicted directly using random regression forests. The predictions are accumulated in Hough images which are treated as likelihood distributions where maxima correspond to joint location hypotheses. Our approach is evaluated on a publicly available dataset with good results. © Springer-Verlag Berlin Heidelberg 2013.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
AuthorsEmailORCID
Holt, BUNSPECIFIEDUNSPECIFIED
Bowden, RUNSPECIFIEDUNSPECIFIED
Date : 1 January 2013
Identification Number : 10.1007/978-3-642-38241-3_27
Additional Information : The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-38241-3_27
Depositing User : Symplectic Elements
Date Deposited : 17 Nov 2015 18:02
Last Modified : 17 Nov 2015 18:02
URI: http://epubs.surrey.ac.uk/id/eprint/808960

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