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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Statistical Models for Text Segmentation
Machine Learning - Special issue on natural language learning
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MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Clustering by Scale-Space Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Advances in domain independent linear text segmentation
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
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ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Hierarchical segmentation using latent semantic indexing in scale space
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
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ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Temporal event clustering for digital photo collections
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Video segmentation combining similarity analysis and classification
Proceedings of the 12th annual ACM international conference on Multimedia
Temporal event clustering for digital photo collections
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Towards a Smarter Meeting Record--Capture and Access of Meetings Revisited
Multimedia Tools and Applications
vADeo: video advertising system
Proceedings of the 15th international conference on Multimedia
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This paper describes a new unified representation for the informa驴tion in a video. We reduce the dimensionality of the signal with either a singular-value decomposition (on the semantic and image data) or mel-frequency cepstral coefficients (on the audio data) and then concatenate the vectors to form a multi-dimensional represen驴tation of the video. Using scale-space techniques we find large jumps in the video's path, which we call edges. We use these tech驴niques to analyze the temporal properties of the audio and image data in a video. This analysis creates a hierarchical segmentation of the video, or a table-of-contents, from the audio, semantic and image data.