Deep Learning for Assistive Computer Vision

Marco Leo, Antonino Furnari, Gérard G. Medioni, Mohan M. Trivedi, Giovanni Maria Farinella

Abstract: This paper revises the main advances in assistive computer vision recently fostered by deep learning. To this aim, we first discuss how the application of deep learning in computer vision has contributed to the development of assistive techinologies, then analyze the recent advances in assistive technologies achieved in five main areas, namely, object classification and localization, scene understanding, human pose estimation and tracking, action/event recognition and anticipation. The paper is concluded with a discussion and insights for future directions.