Summarization of Egocentric Moving Videos for Generating Walking Route Guidance

In this paper, we propose a method to summarize an egocentric moving video (a video recorded by a moving wearable camera) for generating a walking route guidance video. To summarize an egocentric video, we analyze it by applying pedestrian crosswalk detection as well as ego-motion classification, and estimate an importance score of each section of the given video. Based on the estimated importance scores, we dynamically control video playing speed instead of generating a summarized video file in advance. In the experiments, we prepared an egocentric moving video dataset including more than one-hour-long videos totally, and evaluated crosswalk detection and ego-motion classification methods. Evaluation of the whole system by user study has been proved that the proposed method is much better than a simple baseline summarization method without video analysis.