Monocular Vision based Particle Filter Localization in Urban Environments

Abstract

This thesis presents the design and experimental result of a monocular vision based particle filter localization system for urban settings that uses aerial orthoimagery as a reference map. The topics of perception and localization are reviewed along with their modeling using a probabilistic framework. Computer vision techniques used to create the feature map and to extract features from camera images are discussed. Localization results indicate that the design is viable.