Face Annotation for Family Photo Album Management

In this paper, we propose a framework to semi-automatically annotate faces in family photo albums. The core of the framework is the features used to define face similarity and this results in the learning algorithm used to refine automatic face annotation. We have adopted similarity based search and relevance feedback ideas developed for content-based image retrieval and a set of simple yet effective color and texture based features, in addition to the traditional face recognition features, in performing candidate annotation search. The experimental evaluation of the proposed approach has been conducted with a family album of 1707 photos and the results show that the proposed approach is an effective and efficient one for semi-automatic family photo album annotation.

[1]  Shih-Fu Chang,et al.  Image Retrieval: Current Techniques, Promising Directions, and Open Issues , 1999, J. Vis. Commun. Image Represent..

[2]  Thomas S. Huang,et al.  Relevance feedback: a power tool for interactive content-based image retrieval , 1998, IEEE Trans. Circuits Syst. Video Technol..

[3]  Anil K. Jain,et al.  Face Detection in Color Images , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Harry Shum,et al.  Statistical Learning of Multi-view Face Detection , 2002, ECCV.

[5]  Vijay V. Raghavan,et al.  An approach to interactive retrieval in face image databases based on semantic attributes , 1994 .

[6]  Jing Huang,et al.  Image indexing using color correlograms , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[7]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.

[8]  Lei Zhang,et al.  A CBIR method based on color-spatial feature , 1999, Proceedings of IEEE. IEEE Region 10 Conference. TENCON 99. 'Multimedia Technology for Asia-Pacific Information Infrastructure' (Cat. No.99CH37030).

[9]  Rama Chellappa,et al.  Human and machine recognition of faces: a survey , 1995, Proc. IEEE.

[10]  Narendra Ahuja,et al.  Detecting Faces in Images: A Survey , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[12]  Yanfeng Sun,et al.  MiAlbum - a system for home photo managemet using the semi-automatic image annotation approach , 2000, MM 2000.

[13]  Margo Seltzer,et al.  The mug-shot search problem: a study of the eigenface metric, search strategies, and interfaces in a system for searching facial image data , 1999 .

[14]  Paul A. Viola,et al.  Robust Real-time Object Detection , 2001 .

[15]  B. Ripley,et al.  Pattern Recognition , 1968, Nature.

[16]  Mary Czerwinski,et al.  PhotoTOC: automatic clustering for browsing personal photographs , 2003, Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint.

[17]  Martin D. Levine,et al.  Face Recognition Using the Discrete Cosine Transform , 2001, International Journal of Computer Vision.

[18]  Markus A. Stricker,et al.  Similarity of color images , 1995, Electronic Imaging.

[19]  C.-C. Jay Kuo,et al.  Texture analysis and classification with tree-structured wavelet transform , 1993, IEEE Trans. Image Process..