  The task of answering questions about images has garnered attention as a
practical service for assisting populations with visual impairments as well as
a visual Turing test for the artificial intelligence community. Our first aim
is to identify the common vision skills needed for both scenarios. To do so, we
analyze the need for four vision skills---object recognition, text recognition,
color recognition, and counting---on over 27,000 visual questions from two
datasets representing both scenarios. We next quantify the difficulty of these
skills for both humans and computers on both datasets. Finally, we propose a
novel task of predicting what vision skills are needed to answer a question
about an image. Our results reveal (mis)matches between aims of real users of
such services and the focus of the AI community. We conclude with a discussion
about future directions for addressing the visual question answering task.
