  We aim to develop an AI agent that can watch video clips and have a
conversation with human about the video story. Developing video understanding
intelligence is a significantly challenging task, and evaluation methods for
adequately measuring and analyzing the progress of AI agent are lacking as
well. In this paper, we propose the Video Turing Test to provide effective and
practical assessments of video understanding intelligence as well as
human-likeness evaluation of AI agents. We define a general format and
procedure of the Video Turing Test and present a case study to confirm the
effectiveness and usefulness of the proposed test.

Artificial Intelligence;Computer Vision and Pattern Recognition;Human-Computer Interaction