Abstract

The methodologies presented in this thesis address the problem of blind people rehabilitation through assistive technologies. In overall terms, the basic and principal needs that a blind individual might be concerned with can be confined to two components, namely (i) navigation/ obstacle avoidance, and (ii) object recognition. Having a close look at the literature, it seems clear that the former category has been devoted the biggest concern with respect to the latter one. Moreover, the few contributions on the second concern tend to approach the recognition task on a single predefined class of objects. Furthermore, both needs, to the best of our knowledge, have not been embedded into a single prototype. In this respect, we put forth in this thesis two main contributions. The first and main one tackles the issue of object recognition for the blind, in which we propose a ‘coarse recognition’ approach that proceeds by detecting objects in bulk rather than focusing on a single class. Thus, the underlying insight of the coarse recognition is to list the bunch of objects that likely exist in a camera-shot image (acquired by the blind individual with an opportune interface, e.g., voice recognition synthesis-based support), regardless of their position in the scene. It thus trades the computational time with object information details as to lessen the processing constraints. As for the second contribution, we further incorporate the recognition algorithm, along with an implemented navigation system that is supplied with a laser-based obstacle avoidance module. Evaluated on image datasets acquired in indoor environments, the recognition schemes have exhibited, with little to mild disparities with respect to one another, interesting results in terms of either recognition rates or processing gap. On the other hand, the navigation system has been assessed in an indoor site and has revealed plausible performance and flexibility with respect to the usual blind people’s mobility speed. A thorough experimental analysis is hereby provided alongside laying the foundations for potential future research lines, including object recognition in outdoor environments.