RT Conference Proceedings
T1 Mid-level feature set for specific event and anomaly detection in crowded scenes
A1 Calle Silos, Fernando de la
A1 González Díaz, Iván
A1 Díaz de María, Fernando
AB In this paper we propose a system for automatic detection of specific events and abnormal behaviors in crowded scenes. In particular, we focus on the parametrization by proposing a set of mid-level spatio-temporal features that successfully model the characteristic motion of typical events in crowd behaviors. Furthermore, due to the fact that some features are more suitable than others to model specific events of interest, we also present an automatic process for feature selection. Our experiments prove that the suggested feature set works successfully for both explicit event detection and distance-based anomaly detection tasks. The results on PETS for explicit event detection are generally better than those previously reported. Regarding anomaly detection, the proposed method performance is comparable to those of state-of-the-art method for PETS and substantially better than that reported for Web dataset.
PB IEEE
SN 978-1-4799-2341-0
YR 2013
FD 2013
LK https://hdl.handle.net/10016/21587
UL https://hdl.handle.net/10016/21587
LA eng
NO Proceedings of: 20th IEEE International Conference on Image Processing (ICIP 2013). Melbourne, Australia, September 15-18, 2013.
DS e-Archivo
RD 1 jul. 2024