Summarising video data is essential to enable content-based video indexing and retrieval. A novel graph theoretic approach is presented to extract representative key frames corresponding to the shortest path of the graph for each shot. We distinguish further amongst paths of similar weight by examining the standard deviation of their constituent edge weights which improves the distribution of the selected key frames. The perceived camera motions contained within each shot are also annotated to introduce a further level of indexing and searching video content.
|Translated title of the contribution||Video Indexing using Motion Estimation|
|Title of host publication||Unknown|
|Pages||659 - 668|
|Number of pages||9|
|Publication status||Published - Sep 2003|