In this paper we propose a novel video segmentation algorithm that is capable of reliably detecting both types of dissolves in addition to cuts and wipes based on the analysis of spatio-temporal behaviors of Joint Probability Images (JPIs). Experimental results for identifying scene transitions in various video clips that contain moderate and significant amounts of movements are demonstrated.  Video segmentation is a preprocessing step for video analysis and indexing. Detection of scene transitions concerns itself with locating boundaries between clips of different visual contents from a raw video. Reliable video segmentation is crucial for ensuing video analysis tasks. Most existing methods for scene change detection are based on low-or intermediate-level visual cues such as color histogram, edge map, texture, and motion vectors. Several color histogram-based algorithms, e.g., [ 11, have been proposed where clear scene cuts or special effects are claimed on the color histogram difference of a series of video frames. Zabih er al. [2] described an edge feature based algorithm where scene transitions are detected based on the emergence or disappearance of edges. To address the issue of global illumination variations inside one clip, we [3] developed a normalized chromaticity based algorithm which can detect scene changes via a binary search with valuable effectiveness and efficiency. Ngo, Pong and Chin [4] presented a spatio-temporal method for gradual scene changes. Spatially, a stripe (or often a row or column) from each video frame is extracted. With time, the stripes form a spatio-temporal image, i.e., the video slice. Good results were obtained by using a Markov energy model to locate the trajectories of wipes in the spatio-temporal image. For dissolves, the variance in the slice will change and form a concave upward parabola. However, it appeared to be evasive. Constrained by the visual cues employed, so far most scene change detection methods can only report that either a clear cut or a gradual transition is present. A reliable method for detecting dissolves is still lacking.
In REF Li and Wei propose a dissolve detection method based on the analysis of Joint probability Images.
Spatio-temporal joint probability images for video segmentation
Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101)
Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101)
Computer Science