TY  - CONF
AU  - Victor Campmany
AU  - Sergio Silva
AU  - Juan Carlos Moure
AU  - Toni Espinosa
AU  - David Vazquez
AU  - Antonio Lopez
A2  - GTC
PY  - 2016//
TI  - GPU-based pedestrian detection for autonomous driving
BT  - GPU Technology Conference
KW  - Pedestrian Detection
KW  - GPU
N2  - Pedestrian detection for autonomous driving is one of the hardest tasks within computer vision, and involves huge computational costs. Obtaining acceptable real-time performance, measured in frames per second (fps), for the most advanced algorithms is nowadays a hard challenge. Taking the work in [1] as our baseline, we propose a CUDA implementation of a pedestrian detection system that includes LBP and HOG as feature descriptors and SVM and Random forest as classifiers. We introduce significant algorithmic adjustments and optimizations to adapt the problem to the NVIDIA GPU architecture. The aim is to deploy a real-time system providing reliable results.
L1  - http://refbase.cvc.uab.es/files/CSM2016.pdf
N1  - ADAS; 600.085; 600.082; 600.076
ID  - Victor Campmany2016
ER  -