Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
PanoramaExcerpts: extracting and packing panoramas for video browsing
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
Locally adaptive dimensionality reduction for indexing large time series databases
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Hyper-rectangle based segmentation and clustering of large video data sets
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Intelligent multimedia computing and networking
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Fast Time Sequence Indexing for Arbitrary Lp Norms
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Multimedia Systems - Special section on video libraries
On Similarity-Based Queries for Time Series Data
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Similarity Search for Multidimensional Data Sequences
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Detection of video sequences using compact signatures
ACM Transactions on Information Systems (TOIS)
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In this paper, we investigate the similarity search methods for large video data sets that are the collection of video clips. A video clip, a sequence of video frames describing a particular event, is represented by a sequence in a multidimensional data space. Each video clip is partitioned into video segments considering temporal relationship among frames, and then similar segments of the clip are grouped into video clusters. Based on these video segments and clusters, we define similarity functions and present two similarity search methods: the HR (hyper-rectangle)-search and the RP (representative point)- search. Experiments on synthetic sequences as well as real video clips show the effectiveness of our proposed methods.