Image set-based face recognition: A local multi-keypoint descriptor-based approach

Na Liu, Meng Hui LIM, Pong Chi YUEN, Jian Huang Lai

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

Image-set-based face recognition has recently attracted much attention due to widespread of surveillance and video retrieval applications. Extraction of partial and misaligned face images from a video is relatively common in unconstrained scenarios and in the presence of detection/localization error, respectively. However, existing face recognition techniques that consider holistic image-set representation would not perform well under such conditions. In this paper, we introduce a local image-set-based face recognition approach to address this issue, where each image set is represented by a cluster set of keypoint descriptors and similarity between image sets is measured by the distance between the corresponding sets of clusters. Our representation is robust to misalignment because the extraction of descriptors is carried out without respect to the absolute face position. Additionally, our approach is robust to partial face occlusion due to that (1) descriptors corresponding to non-occluded keypoints are not affected by the occluded keypoints, (2) matching decision is contributed only by distances between the matched cluster pairs corresponding to the non-occluded facial parts. Extensive experiment evaluation shows that our approach is able to achieve very promising recognition rates.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2013
Pages160-165
Number of pages6
DOIs
Publication statusPublished - 2013
Event2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2013 - Portland, OR, United States
Duration: 23 Jun 201328 Jun 2013

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2013
Country/TerritoryUnited States
CityPortland, OR
Period23/06/1328/06/13

Scopus Subject Areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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