Computer Vision for Assistive Technologies

In the last decades there has been a tremendous increase in demand for Assistive Technologies (AT) useful to overcome functional limitations of individuals and to improve their quality of life. As a consequence, different research papers addressing the development of assistive technologies have appeared into the literature pushing the need to organize and categorize them taking into account the application assistive aims. Several surveys address the categorization problem for works concerning a specific need, hence giving the overview on the state of the art technologies supporting the related function for the individual. Unfortunately, this ``user-need oriented'' way of categorization considers each technology as a whole and then a deep and critical explanation of the technical knowledge used to build the operative tasks as well as a discussion on their cross-contextual applicability is completely missing making existing surveys unlikely to be technically inspiring for functional improvements and to explore new technological frontiers.To overcome this critical drawback, in this paper an original ``task oriented'' way to categorize the state of the art of the AT works has been introduced: it relies on the split of the final assistive goals into tasks that are then used as pointers to the works in literature in which each of them has been used as a component. In particular this paper concentrates on a set of cross-application Computer Vision tasks that are set as the pivots to establish a categorization of the AT already used to assist some of the user's needs. For each task the paper analyzes the Computer Vision algorithms recently involved in the development of AT and finally it tries to catch a glimpse of the possible paths in the short and medium term that could allow a real improvement of the assistive outcomes.