| ID | 34106 |
| FullText URL | |
| Author | |
| Abstract | Reformulating the Costeira-Kanade algorithm as a pure mathematical theorem independent of the Tomasi-Kanade factorization, we present a robust segmentation algorithm by incorporating such techniques as dimension correction, model selection using the geometric AIC, and least-median fitting. Doing numerical simulations, we demonstrate that oar algorithm dramatically outperforms existing methods. It does not involve any parameters which need to be adjusted empirically |
| Note | Digital Object Identifier: 10.1109/ICCV.2001.937679
Published with permission from the copyright holder. This is the institute's copy, as published in Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on, 7-14 July 2001, Volume: 2, Pages 586-591. Publisher URL:http://dx.doi.org/10.1109/ICCV.2001.937679 Copyright © 2001 IEEE. All rights reserved. |
| Published Date | 2001-7
|
| Publication Title |
Computer Vision
|
| Start Page | 586
|
| End Page | 591
|
| Content Type |
Journal Article
|
| language |
English
|
| Refereed |
True
|
| DOI | |
| Submission Path | electrical_engineering/117
|
