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https://hdl.handle.net/10356/98388
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lu, Jiwen | en |
dc.contributor.author | Hu, Junlin | en |
dc.contributor.author | Zhou, Xiuzhuang | en |
dc.contributor.author | Shang, Yuanyuan | en |
dc.contributor.author | Tan, Yap Peng | en |
dc.contributor.author | Wang, Gang | en |
dc.date.accessioned | 2013-07-29T07:40:32Z | en |
dc.date.accessioned | 2019-12-06T19:54:42Z | - |
dc.date.available | 2013-07-29T07:40:32Z | en |
dc.date.available | 2019-12-06T19:54:42Z | - |
dc.date.copyright | 2012 | en |
dc.date.issued | 2012 | en |
dc.identifier.citation | Lu, J., Hu, J., Zhou, X., Shang, Y., Tan, Y. P., Wang, G., et al. (2012). Neighborhood repulsed metric learning for kinship verification. 2012 IEEE Conference on Computer Vision and Pattern Recognition. | en |
dc.identifier.uri | https://hdl.handle.net/10356/98388 | - |
dc.description.abstract | Kinship verification from facial images is a challenging problem in computer vision, and there is a very few attempts on tackling this problem in the literature. In this paper, we propose a new neighborhood repulsed metric learning (NRML) method for kinship verification. Motivated by the fact that interclass samples (without kinship relations) with higher similarity usually lie in a neighborhood and are more easily misclassified than those with lower similarity, we aim to learn a distance metric under which the intraclass samples (with kinship relations) are pushed as close as possible and interclass samples lying in a neighborhood are repulsed and pulled as far as possible, simultaneously, such that more discriminative information can be exploited for verification. Moreover, we propose a multiview NRM-L (MNRML) method to seek a common distance metric to make better use of multiple feature descriptors to further improve the verification performance. Experimental results are presented to demonstrate the efficacy of the proposed methods. | en |
dc.description.sponsorship | ASTAR (Agency for Sci., Tech. and Research, S’pore) | en |
dc.language.iso | en | en |
dc.rights | © 2012 IEEE. | en |
dc.subject | DRNTU::Engineering::Electrical and electronic engineering | en |
dc.title | Neighborhood repulsed metric learning for kinship verification | en |
dc.type | Conference Paper | en |
dc.contributor.school | School of Electrical and Electronic Engineering | en |
dc.contributor.conference | IEEE Conference on Computer Vision and Pattern Recognition (2012 : Providence, Rhode Island, US) | en |
dc.identifier.doi | 10.1109/CVPR.2012.6247978 | en |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
Appears in Collections: | EEE Conference Papers |
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