Application of the temporal aggregation and pre-categorization of news video shots to reduce the time of content analysis

Content-based indexing methods need to analyze all frames of a video. Because such a procedure is extremely time consuming the indexing may be limited to the key-frames, i.e. to only one or to a few frames for every shot or for every video scene. The detection of the key-frame of a shot or of a scene requires very effective temporal segmentation methods. Content-based indexing of videos is based on the automatic detection of a video structure. A video shot is the main structural video unit. The temporal aggregation results in grouping of shots into scenes of a given category. Moreover, the determination of the most likely category on the basis of time relations also reduces the analysis time enabling us to apply the adequate method of content-based indexing. The main problem is to select report shots and non-report shots because usually different indexing strategies should be applied. The paper examines the usefulness of the temporal aggregation method and pre-categorization of shots in news videos to reduce processing time taken by a very time-consuming content-based video indexing process.