Reconstructing a dynamic surface from video sequences using graph cuts in 4D space-time

Tianli Yu, Ning Xu, Narendra Ahuja

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper is concerned with the problem of dynamically reconstructing the 3D surface of an object undergoing non-rigid motion. The problem is cast as reconstructing a continuous optimal 3D hyper-surface in 4D space-time from a set of calibrated video sequences. The imaging model of video cameras in 4D space-time is derived and a photo-inconsistency cost function is defined for a hyper-surface in the 4D space-time. We use a 4D node-cut algorithm to find a global minimum of the cost function and obtain the corresponding optimal hyper-surface. Experimental results show that the proposed algorithm is effective in recovering continuously changing shapes and exhibits good noise resistance.

Original languageEnglish (US)
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages245-248
Number of pages4
DOIs
StatePublished - 2004
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: Aug 23 2004Aug 26 2004

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2
ISSN (Print)1051-4651

Other

OtherProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
Country/TerritoryUnited Kingdom
CityCambridge
Period8/23/048/26/04

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Fingerprint

Dive into the research topics of 'Reconstructing a dynamic surface from video sequences using graph cuts in 4D space-time'. Together they form a unique fingerprint.

Cite this