Conference Paper: Accurate foreground segmentation without pre-learning
| Title | Accurate foreground segmentation without pre-learning |
|---|---|
| Authors | Kuang, Z1 Zhou, H1 Wong, KKY1 |
| Keywords | Segmentation Contrast attenuation Foreground segmentation Graph cut Automatic algorithms |
| Issue Date | 2011 |
| Publisher | IEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001790 |
| Citation | The 6th International Conference on Image and Graphics (ICIG 2011), Hefei, Anhui, China, 12-15 August 2011. In Proceedings of the 6th ICIG, 2011, p. 331-337 [How to Cite?] DOI: http://dx.doi.org/10.1109/ICIG.2011.150 |
| Abstract | Foreground segmentation has been widely used in many computer vision applications. However, most of the existing methods rely on a pre-learned motion or background model, which will increase the burden of users. In this paper, we present an automatic algorithm without pre-learning for segmenting foreground from background based on the fusion of motion, color and contrast information. Motion information is enhanced by a novel method called support edges diffusion (SED) , which is built upon a key observation that edges of the difference image of two adjacent frames only appear in moving regions in most of the cases. Contrasts in background are attenuated while those in foreground are enhanced using gradient of the previous frame and that of the temporal difference. Experiments on many video sequences demonstrate the effectiveness and accuracy of the proposed algorithm. The segmentation results are comparable to those obtained by other state-of-the-art methods that depend on a pre-learned background or a stereo setup. © 2011 IEEE. |
| ISBN | 978-0-7695-4541-7 |
| DOI | http://dx.doi.org/10.1109/ICIG.2011.150 |
| References | References in Scopus |
| dc.contributor.author | Kuang, Z |
|---|---|
| dc.contributor.author | Zhou, H |
| dc.contributor.author | Wong, KKY |
| dc.date.accessioned | 2011-08-26T14:30:33Z |
| dc.date.available | 2011-08-26T14:30:33Z |
| dc.date.issued | 2011 |
| dc.description.abstract | Foreground segmentation has been widely used in many computer vision applications. However, most of the existing methods rely on a pre-learned motion or background model, which will increase the burden of users. In this paper, we present an automatic algorithm without pre-learning for segmenting foreground from background based on the fusion of motion, color and contrast information. Motion information is enhanced by a novel method called support edges diffusion (SED) , which is built upon a key observation that edges of the difference image of two adjacent frames only appear in moving regions in most of the cases. Contrasts in background are attenuated while those in foreground are enhanced using gradient of the previous frame and that of the temporal difference. Experiments on many video sequences demonstrate the effectiveness and accuracy of the proposed algorithm. The segmentation results are comparable to those obtained by other state-of-the-art methods that depend on a pre-learned background or a stereo setup. © 2011 IEEE. |
| dc.description.nature | published_or_final_version |
| dc.description.other | The 6th International Conference on Image and Graphics (ICIG 2011), Hefei, Anhui, China, 12-15 August 2011. In Proceedings of the 6th ICIG, 2011, p. 331-337 |
| dc.identifier.citation | The 6th International Conference on Image and Graphics (ICIG 2011), Hefei, Anhui, China, 12-15 August 2011. In Proceedings of the 6th ICIG, 2011, p. 331-337 [How to Cite?] DOI: http://dx.doi.org/10.1109/ICIG.2011.150 |
| dc.identifier.doi | http://dx.doi.org/10.1109/ICIG.2011.150 |
| dc.identifier.epage | 337 |
| dc.identifier.hkuros | 191682 |
| dc.identifier.isbn | 978-0-7695-4541-7 |
| dc.identifier.scopus | eid_2-s2.0-80052995268 |
| dc.identifier.spage | 331 |
| dc.identifier.uri | http://hdl.handle.net/10722/137652 |
| dc.language | eng |
| dc.publisher | IEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001790 |
| dc.publisher.place | United States |
| dc.relation.ispartof | International Conference on Image and Graphics Proceedings |
| dc.relation.references | References in Scopus |
| dc.rights | International Conference on Image and Graphics Proceedings. Copyright © IEEE Computer Society. |
| dc.rights | ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
| dc.rights | Creative Commons: Attribution 3.0 Hong Kong License |
| dc.subject | Segmentation |
| dc.subject | Contrast attenuation |
| dc.subject | Foreground segmentation |
| dc.subject | Graph cut |
| dc.subject | Automatic algorithms |
| dc.title | Accurate foreground segmentation without pre-learning |
| dc.type | Conference_Paper |
Author Affiliations
- The University of Hong Kong