Shape-based pedestrian detection and localization

Abstract

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 to estimate the localization of pedestrians using a Kalman filter estimator.