Name
Abstract | ||
|---|---|---|
This paper presents an approach to count the number of people that enters or leaves metro trains. This is a challenging scenario where usually people crowd around the train doors, and therefore it is not possible a direct approach that segments and counts individuals. The proposed technique is based on a statistical analysis of the flow obtained from the motion vectors at corner points. The method has been evaluated on metro sequences showing an average error below 5% in real operational conditions. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICIP.2009.5414002 | ICIP |
Keywords | Field | DocType |
real operational condition,motion vector,corner point,proposed technique,direct approach,statistical analysis,traffic engineering computing,surveillance,image sequence analysis,statistical video analysis,people crowd,image sequences,challenging scenario,metro sequences,people counting,metro train,corner detection,metro trains,average error,crowds counting,video surveillance,operant conditioning,calibration,feature extraction,radiation detectors,pixel | Crowds,Direct method,Computer vision,Corner detection,Computer science,Feature extraction,Artificial intelligence,Pixel,Train,Statistical analysis,Doors | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4244-5655-0 | 978-1-4244-5655-0 | 9 |
PageRank | References | Authors |
0.50 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonio Albiol | 1 | 161 | 13.49 |
| Alberto Albiol | 2 | 259 | 18.99 |
| Julia Silla | 3 | 9 | 0.84 |