Understanding Visual Impairment: A CA-CV Approach for Cognitive Computer Vision

Partially sighted people face multiple challenges in their daily lives. For example, they are not confident about their interactions with other people, mainly because they are not sure of other people's expressions, feelings or intentions. In many cases, this situation results in social issues such as isolation and marginalisation among others. The field of computer vision has attempted to provide solutions to some of the problems people with visual impairment face. Currently, computer vision technologies are able to identify almost any element available in our environment. However, most of the recognition processes are trained based on image classification. The current proposal pushes the boundaries of computer vision (henceforth CV) powered by image categorisation by evolving it to the next stage, namely cognitive computer vision. We aim to develop a computer algorithm to enhance machine vision by incorporating a conversational analytic (henceforth CA) approach. This intelligence will be embedded into a hardware device with the objective of providing real-time feedback to visually impaired users via speech output, thus reducing the gap between technology and human-like augmented senses.