Title :
A unified framework for event summarization and rare event detection
Author :
Kwon, Junseok ; Lee, Kyoung Mu
Author_Institution :
Dept. of EECS, Seoul Nat. Univ., Seoul, South Korea
Abstract :
In this paper, we have proposed an unified framework for event summarization and rare event detection and presented the graph-structure learning and editing method to solve these problems efficiently. The experimental results demonstrated that the proposed method outperformed conventional algorithms in complex and crowded public scenes by exploiting and utilizing causality, frequency, and significance of relations of events.
Keywords :
graph theory; learning (artificial intelligence); video signal processing; complex public scenes; crowded public scenes; editing method; event summarization; graph-structure learning; rare event detection; unified framework; Data mining; Density functional theory; Event detection; Frequency measurement; Hidden Markov models; Markov processes; Proposals;
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
Conference_Location :
Providence, RI
Print_ISBN :
978-1-4673-1226-4
Electronic_ISBN :
1063-6919
DOI :
10.1109/CVPR.2012.6247810