EgoScanning: Quickly Scanning First-Person Videos with Egocentric Elastic Timelines
Booth no: et_0045

Summary: This work presents EgoScanning, a novel video fast-forwarding interface that helps users to find important events from lengthy first-person videos recorded with wearable cameras continuously. This interface is featured by an elastic timeline that adaptively changes playback speeds and emphasizes egocentric cues specific to first-person videos, such as hand manipulations, moving, and conversations with people, based on computer-vision techniques. The interface also allows users to input which of such cues are relevant to events of their interests.

Presenter(s):
Keita Higuchi, The University of Tokyo
Ryo Yonetani, Institute of Industrial Science, The University of Tokyo
Yoichi Sato, Institute of Industrial Science, The University of Tokyo