Comparing images using joint histograms
Multimedia Systems - Special issue on video content based retrieval
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying
IEEE Transactions on Pattern Analysis and Machine Intelligence
A user attention model for video summarization
Proceedings of the tenth ACM international conference on Multimedia
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking users' capture intention: a novel complementary view for home video content analysis
Proceedings of the 13th annual ACM international conference on Multimedia
Summarization of videotaped presentations: automatic analysis of motion and gesture
IEEE Transactions on Circuits and Systems for Video Technology
Playing, performing, reporting: a case study of mobile minimovies composed by teenage girls
Proceedings of the 20th Australasian Conference on Computer-Human Interaction: Designing for Habitus and Habitat
Hierarchical modeling and adaptive clustering for real-time summarization of rush videos
IEEE Transactions on Multimedia
Activity-driven content adaptation for effective video summarization
Journal of Visual Communication and Image Representation
A user-centric system for home movie summarisation
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part I
Enabling portable animation browsing by transforming animations into comics
Proceedings of the 2nd ACM international workshop on Interactive multimedia on mobile and portable devices
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In this paper, we propose a user-adaptive video summarization system which accounts for individual preferences by analyzing contents of the user's personal photo library. Nowadays, it is common practice for people to keep thousands of photos in their PCs, taken with their digital cameras. Due to the similarities in characteristics between video and still photos, we assume that these libraries can be used to infer each user's preferences on video summarization. The system uses image classification techniques to determine which sections of the movie are "important" to the user, and performs summarization by cutting off sections regarded as unimportant, while taking care not to overly disrupt the continuity of the video. We have implemented a prototype of the system, and conducted a series of evaluation tests to assess its effectiveness. The results show that our overall approach has the potential to serve as a powerful automatic/semi-automatic video summarization solution.