Paper
23 December 1997 Video retrieval: content analysis by ImageMiner
Peter Alshuth, Thorsten Hermes, Lutz Voigt, Otthein Herzog
Author Affiliations +
Proceedings Volume 3312, Storage and Retrieval for Image and Video Databases VI; (1997) https://doi.org/10.1117/12.298457
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States
Abstract
In this paper videos are analyzed to get a content-based description of the video. The structure of a given video is useful to index long videos efficiently and automatically. A comparison between shots gives an overview about cut frequency, cut pattern, and scene bounds. After a shot detection the shots are grouped into clusters based on their visual similarity. A time-constraint clustering procedure is used to compare only those shots that are positioned inside a time range. Shots from different areas of the video (e.g., begin/end) are not compared. With this cluster information that contains a list about shots and their clusters it is possible to calculate scene bounds. A labeling of all clusters gives a declaration about the cut pattern. It is easy now to distinguish a dialogue from an action scene. The final content analysis is done by the ImageMinerTM system. The ImageMiner system developed at the University of Bremen of the Image Processing Department of the Center for Computing Technology realizes content-based image retrieval for still images through a novel combination of methods and techniques of computer vision and artificial intelligence. The ImageMiner system consists of three analysis modules for computer vision, namely for color, texture, and contour analysis. Additionally exists a module for object recognition. The output of the object recognition module can be indexed by a text retrieval system. Thus, concepts like forestscene may be searched for. We combine the still image analysis with the results of the video analysis in order to retrieve shots or scenes.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter Alshuth, Thorsten Hermes, Lutz Voigt, and Otthein Herzog "Video retrieval: content analysis by ImageMiner", Proc. SPIE 3312, Storage and Retrieval for Image and Video Databases VI, (23 December 1997); https://doi.org/10.1117/12.298457
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CITATIONS
Cited by 11 scholarly publications and 1 patent.
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KEYWORDS
Video

Image analysis

Visualization

Object recognition

Image retrieval

Image segmentation

Image processing

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