Fast tracking of hierarchical partitions with approximate kl-divergence for geo-temporal organization of personal images

ABSTRACT

Usage of camera-equipped mobile devices raises the need for automatically organizing large personal image collections. We propose here a technique based on a two-level hierarchy of mixture models to automatically organize such a collection with the geo-temporal meta-data attached to each pictures.

REFERENCES

• 1: J. Goldberger and S. Roweis. Hierarchical clustering of a mixture model. In Proc. of Neural Information Processing Systems (NIPS'2004), pages 505--512, 2004.
• 2: Mor Naaman , Yee Jiun Song , Andreas Paepcke , Hector Garcia-Molina, Automatic organization for digital photographs with geographic coordinates, Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries, June 07-11, 2004, Tuscon, AZ, USA [doi>10.1145/996350.996366]
• 3: A. Pigeau , M. Gelgon, Building and tracking hierarchical geographical & temporal partitions for image collection management on mobile devices, Proceedings of the 13th annual ACM international conference on Multimedia, November 06-11, 2005, Hilton, Singapore [doi>10.1145/1101149.1101170]
• 4: Kerry Rodden , Kenneth R. Wood, How do people manage their digital photographs?, Proceedings of the SIGCHI conference on Human factors in computing systems, April 05-10, 2003, Ft. Lauderdale, Florida, USA [doi>10.1145/642611.642682]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing

Keywords:
clustering, image collection management, mobile device