Towards Real Time Egocentric Segment Captioning for The Blind and
  Visually Impaired in RGB-D Theatre Images
Khadidja Delloul Slimane Larabi
In recent years, image captioning and segmentation have emerged as crucial
tasks in computer vision, with applications ranging from autonomous driving to
content analysis. Although multiple solutions have emerged to help blind and
visually impaired people move around their environment, few are applications
that help them understand and rebuild a scene in their minds through text. Most
built models focus on helping users move and avoid obstacles, restricting the
number of environments blind and visually impaired people can be in.
  In this paper, we will propose an approach that helps them understand their
surroundings using image captioning. The particularity of our research is that
we offer them descriptions with positions of regions and objects regarding them
(left, right, front), as well as positional relationships between regions,
while we aim to give them access to theatre plays by applying the solution to
our TS-RGBD dataset.