Human pose extraction from monocular videos using constrained non-rigid factorization
| dc.contributor.author | Shaji, A. | |
| dc.contributor.author | Siddiquie, B. | |
| dc.contributor.author | Chandran, S. | |
| dc.contributor.author | Suter, D. | |
| dc.contributor.conference | British Machine Vision Conference (18th : 2007 : Warwick, UK) | |
| dc.date.issued | 2007 | |
| dc.description.abstract | We focus on the problem of automatically extracting the 3D configuration of human poses from 2D image features tracked over a finite interval of time . This problem is highly non-linear in nature and confounds standard regression techniques. Our approach effectively marries a non-rigid factorization algorithm with prior learned statistical models from archival motion capture database. We show that a stand alone non-rigid factorization algorithm is highly unsuitable for this problem. However, when coupled with the learned statistical model in the form of a constrained non- linear programming method, it yields a substantially better solution. | |
| dc.description.statementofresponsibility | Appu Shaji, Behajt Siddiquie, Sharat Chandran and David Suter | |
| dc.description.uri | http://www.cse.iitb.ac.in/appu/publications.php | |
| dc.identifier.citation | British Machine Vision Conference Proceedings, 2007 | |
| dc.identifier.doi | 10.5244/C.21.92 | |
| dc.identifier.orcid | Suter, D. [0000-0001-6306-3023] | |
| dc.identifier.uri | http://hdl.handle.net/2440/55481 | |
| dc.language.iso | en | |
| dc.publisher | British Machine Vision Association | |
| dc.publisher.place | Online | |
| dc.source.uri | https://doi.org/10.5244/c.21.92 | |
| dc.title | Human pose extraction from monocular videos using constrained non-rigid factorization | |
| dc.type | Conference paper | |
| pubs.publication-status | Published |