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Single-view RGBD-based reconstruction of dynamic human geometry

Malleson, C, Klaudiny, M, Hilton, A and Guillemaut, J-Y (2013) Single-view RGBD-based reconstruction of dynamic human geometry In: IEEE International Conference on Computer Vision Workshops (ICCVW 2013), 2013-12-02 - 2013-12-08, Sydney, NSW.

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We present a method for reconstructing the geometry and appearance of indoor scenes containing dynamic human subjects using a single (optionally moving) RGBD sensor. We introduce a framework for building a representation of the articulated scene geometry as a set of piecewise rigid parts which are tracked and accumulated over time using moving voxel grids containing a signed distance representation. Data association of noisy depth measurements with body parts is achieved by online training of a prior shape model for the specific subject. A novel frame-to-frame model registration is introduced which combines iterative closest-point with additional correspondences from optical flow and prior pose constraints from noisy skeletal tracking data. We quantitatively evaluate the reconstruction and tracking performance of the approach using a synthetic animated scene. We demonstrate that the approach is capable of reconstructing mid-resolution surface models of people from low-resolution noisy data acquired from a consumer RGBD camera. © 2013 IEEE.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
Malleson, C
Klaudiny, M
Hilton, A
Guillemaut, J-Y
Date : 2013
DOI : 10.1109/ICCVW.2013.48
Contributors :
Additional Information : © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 11 Nov 2014 13:53
Last Modified : 31 Oct 2017 17:07

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