Face based image navigation and search

ABSTRACT

People are often the most important subjects in photos, and the ability of finding photos of a particular person easily and quickly in an image collection is highly desired. In this paper, we present a face clustering system which automatically groups photos into clusters, with each cluster containing photos of the same person. This is done based on an advanced face recognition engine and a semi-supervised clustering approach. The system achieved good clustering accuracy when tested on different image sets and by different users. Moreover, features such as adding new images, face cluster navigation and face based image retrieval are added that greatly improve the usability of the system. It also facilitates efficient manual manipulations of clustering results. On top of this technology, image navigation systems have been built, including the "face bubble" visualization which provides one-glance view of a photo collection, and shows the relations among people.

REFERENCES

• 1: K. Messer, J. Kittler, M. Sadeghi, et al., "Face authentication test on the BANCA database," Proc. of International Conf. on Pattern Recognition, vol.4, pp.523--532, Aug. 2004.
• 2: H. Kang and B. Shneiderman, "Visualization methods for personal photo collections: browsing and searching in the PhotoFinder," Proc. of IEEE Conf. on Multimedia and Expo, vol.3, pp.1539--1542, Aug. 2000.
• 3: L. Zhang, L. Chen, M. Li, et al., "Automated annotation of human faces in family albums," ACM International Conf. on Multimedia, pp.355--358, Berkeley, CA, Nov. 2003.
• 4: A. Girgensohn, J. Adcock and L. Wilcox, "Leveraging face recognition technology to find and organize photos," Proc. of Workshop on Multimedia Information Retrieval, ACM Press, pp.99--106, New York, USA, Oct. 2004.
• 5: M. Das and A. Loui, "Automatic face-based image grouping for albuming," IEEE International Conf. on Systems, Man and Cybernetics, vol.4, pp.3726--3731, Oct. 2003.
• 6: M. Zhao, Y. W. Teo, S. Liu, et al., "Automatic person annotation of family photo album," Proc. of 5th Conf. on Image and Video Retrieval, pp.163--172, AZ, July 2006.
• 7: J. Cui, F. Wen, R. Xiao, et al., "EasyAlbum: An interactive photo annotation system based on face clustering and re-ranking," Proc. of CHI Conference, pp.367--376, 2007.
• 8: Y. Ma, X. Ding, "Real-time rotation invariant face detection based on cost-sensitive AdaBoost", Proc. of Intl' Conf. on Image Processing, vol.3, pp.921--924, Barcelona, 2003.
• 9: A. K. Jain and R. C. Dubes, Algorithms for clustering data, Prentice Hall, 1988.
• 10: I. Davidson, S. Ravi, "Agglomerative hierarchical clustering with constraints: theoretical and empirical results," Proc. of 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Oct. 2005.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.9 Applications

General Terms:
Algorithms, Experimentation, Management, Performance

Keywords:
face based image navigation, face based image search, face clustering, image organization, image retrieval