Name
Abstract | ||
|---|---|---|
Automatically detecting violent scenes in videos not only has great potential in several applications (such as movie selection or recommendation for children) but also is a very hot academic research topic. Since 2011, violent scene detection task is one of the core tasks of MediaEval, a benchmarking initiative dedicated to evaluating new algorithms for multimedia access and retrieval1. In this paper, we evaluate the performance of low-level audio/visual features for the violent scene detection task using the datasets and evaluation protocol provided by the MediaEval organizers. Our result report can be used as a baseline for comparison of new algorithms in this task. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SOCPAR.2013.7054129 | SoCPaR |
Keywords | Field | DocType |
video signal processing,violent scene detection,global features,multimedia systems,mediaeval,low-level features evaluation,audio feature,violent scene detection task,feature extraction,video retrieval,evaluation protocol,local features,motion feature,multimedia access,multimedia retrieval,motion pictures,histograms,visualization | Histogram,Computer vision,Computer science,Visualization,Feature extraction,Artificial intelligence,Benchmarking | Conference |
ISBN | Citations | PageRank |
978-1-4799-3399-0 | 0 | 0.34 |
References | Authors | |
9 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vu Lam | 1 | 39 | 5.94 |
| Duy-dinh Le | 2 | 213 | 38.89 |
| Sang Phan Le | 3 | 1 | 0.68 |
| Shin'ichi Satoh | 4 | 2093 | 277.41 |
| Due Arm Duong | 5 | 0 | 0.34 |
| Thanh Duc Ngo | 6 | 82 | 22.24 |