
The purpose of this work is to discuss possible methods to retrieve a frame in a source video sequence starting from a given image query (for example, a screen shot of a movie scene). In order to do that, we develop and test different approaches that rely on SIFT local descriptors. First, we briefly recall the SIFT algorithm and propose a straightforward way to use it in order to find a few candidate frames which are similar to the query image. Then, we propose an improvement of this method by focusing on the moving regions to filter out the irrelevant features. Finally, we formulate a different way to detect the right candidate using a geometric approach that accounts for the relative position of the points of interest.
T57-57.97, Applied mathematics. Quantitative methods, QA1-939, Mathematics
T57-57.97, Applied mathematics. Quantitative methods, QA1-939, Mathematics
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
