3D motion reconstruction for real-world camera motion

Yingying Zhu, Mark Cox, Simon Lucey

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

42 Scopus citations

Abstract

This paper addresses the problem of 3D motion reconstruction from a series of 2D projections under low reconstructibility. Reconstructibility defines the accuracy of a 3D reconstruction from 2D projections given a particular trajectory basis, 3D point trajectory, and 3D camera center trajectory. Reconstructibility accuracy is inherently related to the correlation between point and camera trajectories. Poor correlation leads to good reconstruction, high correlation leads to poor reconstruction. Unfortunately, in most real-world situations involving non-rigid objects (e.g. bodies), camera and point motions are highly correlated (i.e., slow and smooth) resulting in poor reconstructibility. In this paper, we propose a novel approach for 3D motion reconstruction of non-rigid body motion in the presence of real-world camera motion. Specifically we: (i) propose the inclusion of a small number of keyframes in the video sequence from which 3D coordinates are inferred/estimated to circumvent ambiguities between point and camera motion, and (ii) employ a L 1 penalty term to enforce a spar-sity constraint on the trajectory basis coefficients so as to ensure our reconstructions are consistent with the natural compressibility of human motion. We demonstrate impressive 3D motion reconstruction for 2D projection sequences with hitherto low reconstructibility.

Original languageEnglish
Title of host publication2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
PublisherIEEE Computer Society
Pages1-8
Number of pages8
ISBN (Print)9781457703942
DOIs
StatePublished - 2011

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

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