Applying audio description for context understanding of surveillance videos by people with visual impairments

Use of surveillance cameras as a monitoring tool for home environments, elderly, and children has becoming a common practice. However, people with visual impairments have difficulties in using this kind of device because it relies only on visual information. Towards solving this problem, this work aims to propose a solution that combines deep learning techniques for object recognition in the video and the use of the accessibility resource called audio description in order to produce a narrative of the detected information. The result is a surveillance system based on the narratives of video objects that provides useful contextual information about the environment for visually impaired people. Experiments with demos are given to verify and validate such a system.