Poorly maintained sidewalks, missing curb ramps, and other obstacles pose considerable accessibility challenges; however, there are currently few, if any, mechanisms to determine accessible areas of a city a priori. 

In the first half of the presentation, I will talk about our investigation of the feasibility of using untrained crowd workers from Amazon Mechanical Turk (turkers) to find, label, and assess sidewalk accessibility problems in Google Street View imagery. Our work effectively demonstrates a promising new, highly scalable method for acquiring knowledge about sidewalk accessibility.

In the latter half, I will discuss the future works as well as open research questions related in the field of computer vision.