Improving Scene Detection Algorithms Using New Similarity Measures

The creation process of interactive non-linear videos affords the definition of scenes which are connected in a scene graph. These might be available in form of raw material (shots) or need to be extracted from existing films. In the latter case, the scenes have to be defined by the author in a time-consuming process. A semi-automated scene extraction helps the user perform this task. Detected shots and scenes may be corrected in a graphical user interface which is integrated in our authoring tool. To provide satisfying results in the automated scene detection process our main goal was to improve an existing algorithm. Different shot comparison functions were evaluated regarding the overall performance index. The commonly used color histogram intersection was outperformed by a combination of χ-distance and complexity comparison, which unexpectedly attained the best results.