HAH-tree: towards a multidimensional index structure supporting different video modelling approaches in a video database management system

Kasturi Chatterjee and Shu-Ching Chen

International Journal of Information and Decision Sciences, 2010, vol. 2, issue 2, 188-207

Abstract: This paper proposes a multidimensional distance-based index structure for video data which supports the three important video modelling approaches namely hierarchical unit-based modelling, feature-based modelling and video semantics modelling seamlessly within one single framework. These three modelling techniques collectively capture and contain the important aspects of the users' information need during content-based video retrieval. The index is built based on the low-level features of the video data, and the hierarchical containment relationships as well as the video semantics are introduced into the index space with an efficient data signature and a stochastic model, respectively. Efficient k-NN algorithms are proposed to emulate popular content-based video retrieval approaches in a multidimensional distance-based index structure. Extensive experimental results demonstrate the capability of the index structure to generate relevant query results with low computational overhead.

Keywords: multidimensional index structure; hierarchical containment relationships; video data models; video database management; video modelling; unit-based modelling; feature-based modelling; video semantics modelling; content-based video retrieval. (search for similar items in EconPapers)
Date: 2010
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