Automatic video scene segmentation based on spatial-temporal clues and rhythm
This addresses the challenge of opaque video content for users needing efficient retrieval, though it appears incremental as it builds on existing segmentation features.
The authors tackled the problem of efficiently segmenting videos into scenes by proposing a method that uses spatial-temporal relationships and shot rhythm, achieving very high accuracy on an 80-minute video.
With ever increasing computing power and data storage capacity, the potential for large digital video libraries is growing rapidly.However, the massive use of video for the moment is limited by its opaque characteristics. Indeed, a user who has to handle and retrieve sequentially needs too much time in order to find out segments of interest within a video. Therefore, providing an environment both convenient and efficient for video storing and retrieval, especially for content-based searching as this exists in traditional textbased database systems, has been the focus of recent and important efforts of a large research community In this paper, we propose a new automatic video scene segmentation method that explores two main video features; these are spatial-temporal relationship and rhythm of shots. The experimental evidence we obtained from a 80 minutevideo showed that our prototype provides very high accuracy for video segmentation.