Video Retrieval by Still-Image Analysis with ImageMiner

The large amount of available multimedia information (e.g. videos, audio, images) requires eecient and eeec-tive annotation and retrieval methods. As videos start playing a more important role in the frame of multimedia, we want to make these available for content-based retrieval. The ImageMiner-System, which was developed at the University of Bremen in the AI group, is designed for content-based retrieval of single images by a new combination of techniques and methods from computer vision and artiicial intelligence. In our approach to make videos available for retrieval in a large database of videos and images there are two necessary steps: First, the detection and extraction of shots from a video, which is done by a histogram based method and second, the construction of the separate frames in a shot to one still single image. This is performed by a mosaicing-technique. The resulting mosaiced image gives a one image visualization of the shot and can be analyzed by the the ImageMiner-System. ImageMiner has been tested on several domains, (e.g. landscape images, technical drawings), which cover a wide range of applications.