Authors:
D. Fernández
;
I. Parra
;
M. A. Sotelo
;
L. M. Bergasa
;
P. Revenga
;
J. Nuevo
and
M. Ocaña
Affiliation:
University of Alcalá, Spain
Keyword(s):
Pedestrian Recognition, Support Vector Machines, Stereovision, Intelligent Transportation Systems.
Related
Ontology
Subjects/Areas/Topics:
Image Processing
;
Informatics in Control, Automation and Robotics
;
Intelligent Transportation Technologies and Systems
;
Robotics and Automation
;
Vision, Recognition and Reconstruction
Abstract:
This paper describes a binocular vision-based pedestrian recognition System. The basic components of pedestrians are first located in the image and then combined with a SVM-based classifier. This poses the problem of pedestrian detection and recognition in real, cluttered road images. Candidate pedestrians are located using a subtractive clustering attention mechanism. A distributed learning approach is proposed in order to better deal with pedestrians variability, illumination conditions, partial occlusions and rotations. The performance of the pedestrian recognition system is enhanced by a multiframe validation process. By doing so, the detection rate is largely increased. A database containing hundreds of pedestrian examples extracted from real traffic images has been created for learning purposes. We present and discuss the results achieved up to date.