Name
Abstract | ||
|---|---|---|
Population growth has made the probability of incidents at large-scale crowd events higher than ever. In the past decades, automated crowd scene analysis done by computer vision has attracted attention. However, severe occlusions and complex crowd behaviors make such analysis a challenge. As a key aspect of crowd scene analysis, a number of works dealing with dense crowd anomaly detection based on computer vision have been presented. This work is a survey of computer vision techniques for analyzing dense crowd scenes. It covers two aspects: crowd density estimation and abnormal event detection. Some problems and perspectives are discussed at the end. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.20965/jaciii.2017.p0235 | JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS |
Keywords | Field | DocType |
survey,anomaly detection,dense crowd scenes,crowd density estimation,abnormal event detection | Computer vision,Anomaly detection,Computer science,Artificial intelligence | Journal |
Volume | Issue | ISSN |
21 | 2 | 1343-0130 |
Citations | PageRank | References |
5 | 0.45 | 41 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junjie Ma | 1 | 5 | 0.45 |
| Yaping Dai | 2 | 23 | 9.51 |
| Kaoru Hirota | 3 | 1634 | 195.49 |