Correlation based video-dissolve detection

We propose a dissolve detection method based on the analysis of a dissolve modeling error that is the difference between an ideally modeled dissolve curve without any correlation and an actual variance curve with a correlation. First, candidate regions are extracted by using the characteristics of a parabola that is downward convex, then the candidate region will be verified based on a dissolve modeling error. If a dissolve modeling error on a candidate region is less than a threshold adaptively determined based on the variances between the candidate regions and the target correlation, the candidate region should be a dissolve region with a correlation less than the target correlation. By considering the correlation between neighbor scenes, the proposed method is able to be a semantic scene-change detector. The proposed algorithm was tested on various types of data and its performance proved to be more accurate and reliable when compared with other commonly used method dissolve modeling error. The proposed algorithm consists of two steps. First, the candidate dissolve regions are extracted using the characteristics of the first and second derivate of a variance curve. In the second step, the candidate regions are verified based on a dissolve modeling error. If the dissolve modeling error for a candidate region is less than a threshold defined by a dissolve modeling error with a target correlation, the candidate region is determined as a dissolve region with a lower correlation than the target correlation, which can be given application-dependently by user or can be used as a control factor of video parsing. The proposed algorithm was tested on a variety of data and the performance proved to be more accurate and reliable when compared with other commonly used method.