Abstract
In this paper, we present a system to detect and track crowds
in a video sequence captured by a camera. In a first step, we
compute optical flows by means of pyramidal Lucas-Kanade
feature tracking. Afterwards, a density based clustering is
used to group similar vectors. In the last step, it is applied a
crowd tracker in every frame, allowing us to detect and track
the crowds. Our system gives the output as a graphic overlay,
i.e it adds arrows and colors to the original frame sequence,
in order to identify crowds and their movements. For the
evaluation, we check when our system detect certains events
on the crowds, such as merging, splitting and collision.
in a video sequence captured by a camera. In a first step, we
compute optical flows by means of pyramidal Lucas-Kanade
feature tracking. Afterwards, a density based clustering is
used to group similar vectors. In the last step, it is applied a
crowd tracker in every frame, allowing us to detect and track
the crowds. Our system gives the output as a graphic overlay,
i.e it adds arrows and colors to the original frame sequence,
in order to identify crowds and their movements. For the
evaluation, we check when our system detect certains events
on the crowds, such as merging, splitting and collision.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Proceedings of the European Signal Processing Conference |
| Vol/bind | 18 |
| Sider (fra-til) | 269-273 |
| ISSN | 2076-1465 |
| Status | Udgivet - aug. 2010 |
| Begivenhed | EUSIPCO 2010 - Aalborg, Danmark Varighed: 23 aug. 2010 → … |
Konference
| Konference | EUSIPCO 2010 |
|---|---|
| Land/Område | Danmark |
| By | Aalborg |
| Periode | 23/08/2010 → … |