Robust, fast object detection systems are critical to the success of next-generation automotive vision systems. An important criteria is that the detection system be easily configurable to a new domain or environment. In this paper, we present work on a general object detection system that can be trained to detect different types of objects; we will focus on the task of pedestrian detection. Th...

and Applied Analysis 3

Automatic detection systems do not perform as well as human observers, even on simple detection tasks. A potential solution to this problem is training vision systems on appropriate regions of interests (ROIs), in contrast to training on predefined and arbitrarily selected regions. Here we focus on detecting pedestrians in static scenes. Our aim is to answer the following question: Can automati...

No part of this journal may be reproduced or used in any form or by any means without written permission from the publisher, except for noncommercial, educational use including classroom teaching purposes. Product or company names used in this journal are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of...

This work presents a vision-based system for detecting and localizing pedestrians in road environments by means of a statistical technique. Initially, attentive vision techniques relying on the search for specific characteristics of pedestrians such as vertical symmetry and strong presence of edges, allow to select interesting regions likely to contain pedestrians. These regions are then used t...

This paper presents the method for detecting pedestrian recently implemented on the ARGO vehicle. The perception of the environment is performed through the sole processing of images acquired from a vision system installed on board of the vehicle: the analysis of a monocular image delivers a first coarse detection, while a distance refinement is performed thanks to a stereo vision technique.