RT Conference Proceedings
T1 Part based pedestrian detection based on logic inference
A1 Olmeda Reino, Daniel
A1 Armingol Moreno, José María
A1 Escalera Hueso, Arturo de la
AB This paper presents an approach on detection of largely occluded pedestrians. From a pair of synchronized cameras in the Visible Light (VL) and Far Infrared (FIR) spectrum individual detections are combined and final confidence is inferred using a small set of logic rules via a Markov Logic Network. Pedestrians not entirely contained in the image or occluded are detected based on the binary classification on subparts of the detection window. The presented method is applied to a pedestrian classification problem in urban environments. The classifier has been tested in an Intelligent Transportation System (ITS) platform as part of an Advanced Driver Assistance Systems (ADAS).
PB IEEE
SN 978-1-4799-2914-6
YR 2013
FD 2013
LK https://hdl.handle.net/10016/23632
UL https://hdl.handle.net/10016/23632
LA eng
NO This work was supported by the Spanish Government through theCicyt projects FEDORA (GRANT TRA2010-20225-C03- 01) and DriverDistraction Detector System (GRANT TRA2011-29454-C03-02), and bythe Comunidad de Madrid through the project SEGVAUTO (S2009/DPI-1509).
DS e-Archivo
RD 1 sept. 2024