Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
6-2015
Abstract
This paper investigates the task of automatically associating faces appearing in images (or videos) with their names. Our novelty lies in the use of celebrity Web images to facilitate the task. Specifically, we first propose a method named Image Matching (IM), which uses the faces in images returned from name queries over an image search engine as the gallery set of the names, and a probe face is classified as one of the names, or none of them, according to their matching scores and compatibility characterized by a proposed Assigning-Thresholding (AT) pipeline. Noting IM could provide guidance for association for the well-established Graph-based Association (GA), we further propose two methods that jointly utilize the two kinds of complementary cues. They are: the early fusion of IM and GA (EF-IMGA) that takes the IM score as an additional information source to help the association in GA, and the late fusion of IM and GA (LF-IMGA) that combines the scores from both IM and GA obtained individually to make the association. Evaluations on datasets of captioned news images and Web videos both show the proposed methods, especially the two fused ones, provide significant improvements over GA.
Keywords
Celebrity image, Multimedia fusion, Name-face association
Discipline
Data Storage Systems | Graphics and Human Computer Interfaces
Research Areas
Intelligent Systems and Optimization
Publication
Proceedings of the 5th ACM International Conference on Multimedia Retrieval, ICMR 2015, Shanghai, China, June 23-26
First Page
623
Last Page
626
ISBN
9781450332743
Identifier
10.1145/2671188.2749401
Publisher
ACM
City or Country
Shanghai
Citation
CHEN, Zhineng; FENG, Bailan; NGO, Chong-wah; JIA, Caiyan; and HUANG, Xiangsheng.
Improving automatic name-face association using celebrity images on the Web. (2015). Proceedings of the 5th ACM International Conference on Multimedia Retrieval, ICMR 2015, Shanghai, China, June 23-26. 623-626.
Available at: https://ink.library.smu.edu.sg/sis_research/6471
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