Robust regression and outlier detection
Robust regression and outlier detection
Algorithms for clustering data
Algorithms for clustering data
Efficient and cost-effective techniques for browsing and indexing large video databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Detecting video shot boundaries up to 16 times faster (poster session)
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
On clustering and retrieval of video shots
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Image analysis and rule-based reasoning for a traffic monitoring system
IEEE Transactions on Intelligent Transportation Systems
A unified framework for object retrieval and mining
IEEE Transactions on Circuits and Systems for Video Technology
Multimedia data mining: state of the art and challenges
Multimedia Tools and Applications
Expert Systems with Applications: An International Journal
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We extend our previous work [1] of the general framework for video data mining to further address the issue such as how to mine video data using motions in video streams. To extract and characterize these motions, we use an accumulation of quantized pixel differences among all frames in a video segment. As a result, the accumulated motions of segment are represented as a two dimensional matrix. Further, we develop how to capture the location of motions occurring in a segment using the same matrix generated for the calculation of the amount. We study how to cluster those segmented pieces using the features (the amount and the location of motions) we extract by the matrix above. We investigate an algorithm to find whether a segment has normal or abnormal events by clustering and modeling normal events, which occur mostly. In addition to deciding normal or abnormal, the algorithm computes Degree of Abnormality of a segment, which represents to what extent a segment is distant to the existing segments in relation with normal events. Our experimental studies indicate that the proposed techniques are promising.