Title: HAH-tree: towards a multidimensional index structure supporting different video modelling approaches in a video database management system
Author: Kasturi Chatterjee, Shu-Ching Chen
Distributed Multimedia Information Systems Laboratory, School of Computing and Information Sciences, Florida International University, Miami, FL 33199, USA.
Distributed Multimedia Information Systems Laboratory, School of Computing and Information Sciences, Florida International University, Miami, FL 33199, USA
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.
Int. J. of Information and Decision Sciences, 2010 Vol.2, No.2, pp.188 - 207
Available online: 27 Feb 2010