  We propose a two-stage unsupervised approach for parsing videos into phases.
We use motion cues to divide the video into coarse segments. Noisy segment
labels are then used to weakly supervise an appearance-based classifier. We
show the effectiveness of the method for phase detection in colonoscopy videos.
