Temporal event clustering for digital photo collections

We present similarity-based methods to cluster digital photos by time and image content. The approach is general, unsupervised, and makes minimal assumptions regarding the structure or statistics of the photo collection. We present results for the algorithm based solely on temporal similarity, and jointly on temporal and content-based similarity. We also describe a supervised algorithm based on learning vector quantization. Finally, we include experimental results for the proposed algorithms and several competing approaches on two test collections. Categories and Subject Descriptors H.5 [Information Interfaces and Presentation]: Multimedia Information Systems; H.3 [Information Storage and Retrieval]: Content Analysis and Indexing—Indexing methods General Terms algorithms, management Keywords digital photo organization, temporal media indexing and segmentation

• Type: Conference
• Year: 2003
• Where: MM
• Authors: Matthew L. Cooper, Jonathan Foote, Andreas Girgensohn, Lynn Wilcox
• Keywords: Digital Photo, MM 2003, Temporal Media Indexing, Temporal Similarity