Abstract:
Finding good representations for videos is becoming increasingly more important to enable an efficient analysis and comparison, with potential applications in sports, sur...Show MoreMetadata
Abstract:
Finding good representations for videos is becoming increasingly more important to enable an efficient analysis and comparison, with potential applications in sports, surveillance, news, or web services. This paper proposes a new representation of videos based on human pose. Rather than looking at conventional features, our method relies only on human pose detections to characterize the video. This approach provides a powerful tool for the efficient analysis of videos of human activities, particularly for video summarization and retrieval. We evaluate the proposed representation on the following tasks: 1) computing video statistics, such as the main poses and viewpoint preferences; 2) partitioning videos into a collection of short clips that will compose the video summary; and 3) retrieving frames or scenes with specific poses from videos. Results show that the proposed approach is able to successfully perform these tasks.
Date of Conference: 04-06 September 2019
Date Added to IEEE Xplore: 21 October 2019
ISBN Information: