In this paper, we first present a theorem that HOSVD-based representation of high-order tensor data provides a robust framework that can be used for a unified 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 flexible 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 finally used to illustrate the robustness and efficiency of the proposed approach to multiple trajectory indexing and retrieval from multi-camera systems.
['Qun Li', 'Xiangqiong Shi', 'Dan Schonfeld']
A general framework for robust HOSVD-based indexing and retrieval with high-order tensor data