Video Navigation Based on Self-Organizing Maps
Content-based video navigation is an efficient method for browsing video information. A common approach is to cluster shots into groups and visualize them afterwards. In this paper, we present a prototype that follows in general this approach. The clustering ignores temporal information and is based on a growing self-organizing map algorithm. They provide some inherent visualization properties such as similar elements can be found easily in adjacent cells. We focus on studying the applicability of SOMs for video navigation support. We complement our interface with an original time bar control providing – at the same time – an integrated view of time and content based information. The aim is to supply the user with as much information as possible on one single screen, without overwhelming him.
KeywordsVideo Content Colour Histogram Winner Neuron Temporal Segmentation Shot Boundary Detection
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