Face Detection and Object Recognition for a Retinal Prosthesis

We describe the recent development of assistive computer vision algorithms for use with the Argus II retinal prosthesis system. While users of the prosthetic system can learn and adapt to the limited stimulation resolution, there exists great potential for computer vision algorithms to augment the experience and significantly increase the utility of the system for the user. To this end, our recent work has focused on helping with two different challenges encountered by the visually impaired: face detection and object recognition. In this paper, we describe algorithm implementations in both of these areas that make use of the retinal prosthesis for visual feedback to the user, and discuss the unique challenges faced in this domain.