RT info:eu-repo/semantics/article
T1 Error analysis in a stereo vision-based pedestrian detection sensor for collision avoidance applications
A1 Fernández Llorca, David
A1 Sotelo Vázquez, Miguel Ángel
A1 Parra Alonso, Ignacio
A1 Ocaña Miguel, Manuel
A1 Bergasa Pascual, Luis Miguel
K1 3D sensors
K1 Automotive industry
K1 Computer vision
K1 Stereo quantization errors
K1 Pedestrian detection
K1 Electrónica
K1 Electronics
AB This paper presents an analytical study of the depth estimation error of a stereo vision-based pedestrian detection sensor for automotive applications such as pedestrian collision avoidance and/or mitigation. The sensor comprises two synchronized and calibrated low-cost cameras. Pedestrians are detected by combining a 3D clustering method with Support Vector Machine-based (SVM) classification. The influence of the sensor parameters in the stereo quantization errors is analyzed in detail providing a point of reference for choosing the sensor setup according to the application requirements. The sensor is then validated in real experiments. Collision avoidance maneuvers by steering are carried out by manual driving. A real time kinematic differential global positioning system (RTK-DGPS) is used to provide ground truth data corresponding to both the pedestrian and the host vehicle locations. The performed field test provided encouraging results and proved the validity of the proposed sensor for being used in the automotive sector towards applications such as autonomous pedestrian collision avoidance.
PB MDPI
SN 1424-8220
YR 2010
FD 2010-04-13
LK http://hdl.handle.net/10017/43548
UL http://hdl.handle.net/10017/43548
LA eng
NO Ministerio de Ciencia e Innovación
DS MINDS@UW
RD 25-abr-2024