Abstract
In this paper we propose a probabilistic approach for the automatic organization of collected pictures aiming at more effective representation in personal photo albums. Images are analyzed and described in two representation spaces, namely, faces and background. Faces are automatically detected, rectified and represented projecting the face itself in a common low dimensional eigenspace. Backgrounds are represented with low-level visual features based on RGB histogram and Gabor filter energy. Face and background information of each image in the collection is automatically organized by mean-shift clustering technique. Given the particular domain of personal photo libraries, where most of the pictures contain faces of a relatively small number of different individuals, clusters tend to be semantically significant beyond containing visually similar data. We report experimental results based on a dataset of about 1000 images where automatic detection and rectification of faces lead to approximately 300 faces. Significance of clustering has been evaluated and results are very encouraging.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Caminati, L., Don, A., et al.: Detection of visual dialog scenes in video content based on structural and semantic features. In: Proc. of International Workshop on Content-based Multimedia Indexing, CBMI (2005)
Abdel-Mottaleb, M., Chen, L.: Content-based photo album management using faces’ arrangement. In: IEEE International Conference on Multimedia and Expo., ICME (2004)
Ardizzone, E., La Cascia, M., Vella, F.: A novel approach to personal photo album representation and management. In: SPIE, vol. 6820 (2008)
Berg, T.L., Berg, A.C., Edwards, J., Maire, M., White, R., Teh, Y.W., Learned-Miller, E., Forsyth, D.A.: Names and faces in the news. In: Proc. of IEEE International Conference on Computer Vision and Pattern Recognition, CVPR (1994)
Bezdek, J.C.: Pattern Recognition with Fuzzy Object Function. Plenum (1981)
Chen, J.Y., Bouman, C.A., Dalton, J.C.: Hierarchical browsing and search of large image databases. IEEE Transaction on Image Processing 9(3), 442–455 (2000)
Cheng, Y.: Mean shift, mode seeking and clustering. IEEE Transaction on Pattern Analysis and Machine Intelligence, 790–799 (August 1995)
Comaniciu, D., Meer, P.: Mean shift: A robust approach toward feature space analysis. IEEE Transaction on Pattern Analysis and Machine Intelligence, 603–619 (May 2002)
Cui, J., Wen, F., Xiao, R., Tian, Y., Tang, X.: Easyalbum: An interactive photo annotation system based on face clustering and re-ranking. In: Proc. of ACM CHI (2007)
Cuiy, J., Wenz, F., Xiaoz, R., Tianx, Y., Tang, X.: Easyalbum: An interactive photo annotation system based on face clustering and re-ranking. In: Proc. of CHI (2007)
Deng, D.: Content based comparison of image collection via distance measuring of self organized maps. In: Proceedings of 10th INternational Multimedia Modelling Conference (2004)
Girgensohn, A., Adcock, J., Wilcox, L.: Leveraging face recognition technology to find and organize photos. In: Proc. of ACM MIR (2004)
Goldberg, J., Gordon, S., Greenspan, H.: Unsupervised image-set clustering using an information theoretic framework. IEEE Transaction on Image Processing (2), 449–458 (2006)
Graham, A., Garcia-Molina, H., Paepcke, A., Winograd, T.: Time as essence for photo browsing through personal digital libraries. In: Proc. of ACM JCDL (2002)
Kang, H., Shneiderman, B.: Visualization methods for personal photo collections: Browsing and searching in the photofinder. In: Proc. of IEEE International Conference on Multimedia and Expo., ICME (2000)
Krishnamachari, S., Abdel-Mottaleb, M.: Hierarchical clustering algorithm for fast image retrieval
Lee, B.N., Chen, W.-Y., Chang, E.Y.: A scalable service for photo annotation, sharing and search. In: Proc. of ACM International Conference on Multimedia (2006)
Li, C.-H., Chiu, C.-Y., Huang, C.-R., Chen, C.-S., Chien, L.-F.: Image content clustering and summarization for photo collections. In: Proceedings of ICME, pp. 1033–1036 (2006)
Naaman, M., Yeh, R.B., Garcia-Molina, H., Paepcke, A.: Leveraging context to resolve identity in photo albums. In: Proc. of ACM JCDL (2005)
Shyu, M.-L., Chen, S.-H., Chen, M., Zhang, C.: A unified framework for image database clustering and content-based retrieval. In: ACM International Workshop On Multimedia Databases archive Proceedings of the 2nd ACM international workshop on Multimedia databases, pp. 19–27 (2004)
Song, Y., Leung, T.: Context-aided human recognition clustering. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3953, pp. 382–395. Springer, Heidelberg (2006)
Spyrou, E., Kapsalas, P., Tolias, G., Mylonas, P., Avrithis, Y., et al.: The cost292 experimental framework for trecvid 2007. In: Proc. of 5th TRECVID Workshop (2007)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proc. of IEEE International Conference on Computer Vision and Pattern Recognition, CVPR (2001)
Wu, K.L., Yang, M.S.: A cluster validity index for fuzzy clustering. Pattern Recognition Letters, 1275–1291 (2005)
Zhang, L., Chen, L., Li, M., Zhang, H.: Automated annotation of human faces in family albums. In: Proc. of ACM International Conference on Multimedia (2003)
Zhang, L., Hu, Y., Li, M., Ma, W., Zhang, H.: Efficient propagation for face annotation in family albums. In: Proc. of ACM International Conference on Multimedia (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ardizzone, E., La Cascia, M., Vella, F. (2010). Unsupervised Clustering in Personal Photo Collections. In: Detyniecki, M., Leiner, U., Nürnberger, A. (eds) Adaptive Multimedia Retrieval. Identifying, Summarizing, and Recommending Image and Music. AMR 2008. Lecture Notes in Computer Science, vol 5811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14758-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-14758-6_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14757-9
Online ISBN: 978-3-642-14758-6
eBook Packages: Computer ScienceComputer Science (R0)