Name
Abstract | ||
|---|---|---|
In this paper, we propose a new application to infer the “cause” of human crowd (scheduled events, sudden accidents and so on) by mobile crowd sensing. The idea is that we leverage our phone-camera-based, crowd-sourced people counting to firstly localize an event with human crowds, and then extract keywords that spatiotemporally correspond to the event from micro blogs such as tweets. Such keywords are further analyzed to find out the most-frequent ones, which can be used to characterize the detected human-crowd event and to estimate its cause. We demonstrate our prototype design using real camera images and tweets to automatically detect the Halloween street party in Tokyo and estimate its human density. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/PERCOMW.2017.7917560 | 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) |
Keywords | Field | DocType |
event detection,crowd detection,camera image fusion,micro blogs,mobile crowd sensing,phone-camera-based people,crowd-sourced people,human-crowd event detection,Tokyo,Halloween street party,human density estimation | Crowds,Computer security,Computer science,Computer network,Real-time computing,Market research | Conference |
ISSN | ISBN | Citations |
2474-2503 | 978-1-5090-4339-2 | 1 |
PageRank | References | Authors |
0.35 | 15 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sohei Kojima | 1 | 1 | 0.35 |
| Akira Uchiyama | 2 | 78 | 14.48 |
| Masumi Shirakawa | 3 | 51 | 7.69 |
| Akihito Hiromori | 4 | 42 | 13.19 |
| Hirozumi Yamaguchi | 5 | 371 | 60.93 |
| Higashino, T. | 6 | 19 | 15.19 |