Medium knowledge-based macro-segmentation of video into sequences
Intelligent multimedia information retrieval
Segment-based approach for subsequence searches in sequence databases
Proceedings of the 2001 ACM symposium on Applied computing
Variable Length Queries for Time Series Data
Proceedings of the 17th International Conference on Data Engineering
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Probabilistic discovery of time series motifs
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Statistical models of video structure for content analysis and characterization
IEEE Transactions on Image Processing
Efficient video similarity measurement with video signature
IEEE Transactions on Circuits and Systems for Video Technology
Rank-test similarity measure between video segments for local descriptors
AMR'06 Proceedings of the 4th international conference on Adaptive multimedia retrieval: user, context, and feedback
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We define a style similarity measure for video documents based on the localization of common elements and on the temporal order in which they appear in each document. Common elements for a couple of compared videos are segments presenting similar behaviors on a subset of low or mid level features extracted for the comparison process. We propose a method to compare two video documents and to extract those similar elements using dynamic programming and one-dimensional morphological operations. The similarity measure is applied on TV-news broadcast to illustrate its behavior.