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Learning to Name Faces: A Multimodal Learning Scheme for Search-Based Face Annotation


Authors: D. Wang, S. C. H. Hoi, P. Wu, J. Zhu, Y. He, and C. Miao
Title: Learning to Name Faces: A Multimodal Learning Scheme for Search-Based Face Annotation
Abstract: Automated face annotation aims to automatically detect human faces from a photo and further name the faces with the corresponding human names. In this paper, we tackle this open problem by investigating a search-based face annotation (SBFA) paradigm for mining large amounts of web facial images freely available on the WWW. Given a query facial image for annotation, the idea of SBFA is to first search for top-n similar facial images from a web facial image database and then exploit these top-ranked similar facial images and their weak labels for naming the query facial image. To fully mine those information, this paper proposes a novel frame-work of Learning to Name Faces (L2NF) – a unified multimodal learning approach for search-based face annotation, which consists of the following major components: (i) we enhance the weak labels of top-ranked similar images by exploiting the “label smoothness" assumption; (ii) we construct the multimodal representations of a facial image by extracting different types of features; (iii) we optimize the distance measure for each type of features using distance metric learning techniques; and finally (iv) we learn the optimal combination of multiple modalities for annotation through a learning to rank scheme. We conduct a set of extensive empirical studies on two real-world facial image databases, in which encouraging results show that the proposed algorithms significantly boost the naming accuracy of search-based face annotation task.
Keywords: Web facial images; Auto face annotation; Supervised learning
Conference Name: 36th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'13)
Location: Dublin, Ireland
Publisher: ACM
Year: 2013
Accepted PDF File: Learning_to_Name_Faces_A_Multimodal_Learning_Scheme_for_Search-Based_Face_Annotation_accepted.pdf
Permanent Link: http://dx.doi.org/10.1145/2484028.2484040
Reference: D. Wang, S. C. H. Hoi, P. Wu, J. Zhu, Y. He, and C. Miao, “Learning to name faces: A multimodal learning scheme for search-based face annotation,” in Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’13). ACM, July–August 2013, pp. 443–452.
bibtex: 
@inproceedings{LILY-c5,
   author 	= {Wang, Dayong and Hoi, Steven C. H. and Wu, Pengcheng and Zhu, Jianke and He, Ying and Miao, Chunyan},
   title 	= {Learning to Name Faces: A Multimodal Learning Scheme for Search-Based Face Annotation},
   booktitle 	= {Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'13)},
   year 	= {2013},
   month	= {July--August}, 
   location 	= {Dublin, Ireland},
   pages 	= {443-452},
   publisher 	= {ACM},
}