Name
Abstract | ||
|---|---|---|
This paper introduces an unusual event detection scheme in various video scenes. The proposed method finds out the video clips that are most different from the others based on the similarity measure. Each video clip is represented by the motion magnitude and direction histograms and color histogram. Without searching key-frames, we calculate the similarity matrix by using \chi^2 difference or chamfer difference as the similarity measure of features in different clips. Finally, we apply n-cut clustering. Clusters with low self-similarity value are reported as unusual events. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/IIH-MSP.2006.44 | IIH-MSP |
Keywords | Field | DocType |
video clip,direction histogram,abnormal event detection,unusual event,n-cut clustering,color histogram,similarity matrix,similarity measure,different clip,chamfer difference,unusual event detection scheme,various video scene,layout,security,bayesian methods,hidden markov models,histograms | Histogram,Computer vision,Pattern recognition,Similarity measure,Color histogram,Computer science,Feature extraction,Artificial intelligence,Motion estimation,Cluster analysis,Hidden Markov model,Bayesian probability | Conference |
ISBN | Citations | PageRank |
0-7695-2745-0 | 3 | 0.40 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chun-Ku Lee | 1 | 10 | 2.16 |
| Meng-Fen Ho | 2 | 50 | 3.01 |
| Wu-Sheng Wen | 3 | 3 | 0.40 |
| Chung-Lin Huang | 4 | 540 | 37.61 |