TY  - CONF
AU  - Diego Cheda
AU  - Daniel Ponsa
AU  - Antonio Lopez
A2  - IV
PY  - 2012//
TI  - Pedestrian Candidates Generation using Monocular Cues
BT  - IEEE Intelligent Vehicles Symposium
SP  - 7
EP  - 12
PB  - IEEE Xplore
KW  - pedestrian detection
N2  - Common techniques for pedestrian candidates generation (e.g., sliding window approaches) are based on an exhaustive search over the image. This implies that the number of windows produced is huge, which translates into a significant time consumption in the classification stage. In this paper, we propose a method that significantly reduces the number of windows to be considered by a classifier. Our method is a monocular one that exploits geometric and depth information available on single images. Both representations of the world are fused together to generate pedestrian candidates based on an underlying model which is focused only on objects standing vertically on the ground plane and having certain height, according with their depths on the scene. We evaluate our algorithm on a challenging dataset and demonstrate its application for pedestrian detection, where a considerable reduction in the number of candidate windows is reached.
SN  - 1931-0587
SN  - 978-1-4673-2119-8
L1  - http://refbase.cvc.uab.es/files/cpl2012d.pdf
UR  - http://dx.doi.org/10.1109/IVS.2012.6232117
N1  - ADAS
ID  - Diego Cheda2012
ER  -