Publication at Faculty of Mathematics and Physics |
2014
Abstract
In this paper, we present an effective yet efficient approach for known-item search in video data. The approach employs feature signatures based on color distribution to represent video key-frames.
At the same time, the feature signatures enable users to intuitively draw simple colored sketches of the desired scene. We describe in detail the video retrieval model and also discuss and carefully optimize its parameters.
Furthermore, several indexing techniques suitable for the model are presented and their performance is empirically evaluated in the experiments. Apart from that, we also investigate a bounding-sphere pruning technique suitable for similarity search in vector spaces.