A general framework for robust HOSVD-based indexing and retrieval with high-order tensor data

In this paper, we rst present a theorem that HOSVD-based representation of high-order tensor data provides a robust framework that can be used for a uni ed representation of the HOSVD of all subtensors. We then propose a general algorithm for robust indexing and retrieval of multiple motion trajectories obtained from a multi-camera system. Guided by our theorem, the unitary transformation matrices of a subtensor can be very well approximated by a subset of unitary matrices corresponding to the same dimensions of the original tensor. As a result, when dealing with exible query structure consisting of an arbitrary number of objects and cameras, instead of recalculating unitary transformation matrices of the corresponding subtensor, we can just employ a subset of the original unitary matrices. Simulation results are nally used to illustrate the robustness and ef ciency of the proposed approach to multiple trajectory indexing and retrieval from multi-camera systems.

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: Qun Li, Xiangqiong Shi, Dan Schonfeld
• Keywords: ICASSP 2011, Original Unitary Matrices, Signal Processing, Unitary Matrices, Unitary Transformation Matrices