Error analysis in a stereo vision-based pedestrian detection sensor for collision avoidance applications
Autores
Fernández Llorca, David; Sotelo Vázquez, Miguel Ángel; Parra Alonso, Ignacio; Ocaña Miguel, Manuel; Bergasa Pascual, Luis MiguelIdentificadores
Enlace permanente (URI): http://hdl.handle.net/10017/43548DOI: 10.3390/s100403741
ISSN: 1424-8220
Editor
MDPI
Fecha de publicación
2010-04-13Patrocinadores
Ministerio de Ciencia e Innovación
Ministerio de Fomento
Cita bibliográfica
Llorca, D.F., Sotelo, M.A., Parra, I., Ocaña, M. & Bergasa, L.M. 2010, "Error analysis in a stereo vision-based pedestrian detection sensor for collision avoidance applications", Sensors, vol. 10, no. 4, pp. 3741-3758
Palabras clave
3D sensors
Automotive industry
Computer vision
Stereo quantization errors
Pedestrian detection
Proyectos
TRA2008-06602-C03 (Ministerio de Ciencia e Innovación)
P9/08 (Ministerio de Fomento)
Tipo de documento
info:eu-repo/semantics/article
Versión
info:eu-repo/semantics/publishedVersion
Versión del editor
https://doi.org/10.3390/s100403741Derechos
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Derechos de acceso
info:eu-repo/semantics/openAccess
Resumen
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.
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