Automatic Movie Content Analysis

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MoCA Project: VisualGREP

VisualGREP research considers the problem of similarity between video sequences. Three basic questions are raised and (partially) answered. Firstly, at what temporal duration can video sequences be compared? The frame, shot, scene and video levels are identified. Secondly, given some image or video feature, what are the requirements on its distance measure and how can it be "easily" transformed into the visual similarity desired by the inquirer? Thirdly, how can video sequences be compared at different levels? A general approach based on either a set or sequence representation with variable degrees of aggregation is proposed and applied recursively over the different levels of temporal resolution. It allows the inquirer to fully control the importance of temporal ordering and duration. The general approach is illustrated by introducing and discussing some of the many possible image and video features. Promising experimental results are presented.

Publications

• Rainer Lienhart, Wolfgang Effelsberg, and Ramesh Jain. VisualGREP: A Systematic Method to Compare and Retrieve Video Sequences. Technical Report TR-97-005, Praktische Informatik IV, University of Mannheim, 1998. [Abstract] [PDF: 138KB]; accepted for publication Kluwer Multimedia Tools and Applications.
• Rainer Lienhart, Wolfgang Effelsberg, and Ramesh Jain. Towards a Visual Grep: A systematic analysis of various methods to compare video sequences. in Storage and Retrieval for Image and Video Databases VI, Ishwar. K. Sethi, Ramesh C. Jain, Editors, Proc. SPIE 3312, pp. 271-282. 1998. [Abstract] [ PDF: 138KB]