Robust HOSVD-Based Multi-Camera Motion Trajectory Indexing and Retrieval

We present a novel method for robust indexing and retrieval of multiple motion trajectories obtained from a multi-camera system. Motion trajectories describe the motion information by recording the objects' coordinates in the video sequence. We generate a four-dimensional tensor representation of multiple motion trajectories from multiple cameras. We subsequently rely on high-order singular value decomposition (HOSVD) for compact representation and dimensionality reduction of the tensor. We show that HOSVD-based representation provides a robust framework that can be used for a unified representation of the HOSVD of all subtensors. We thus demonstrate analytically and experimentally that the proposed HOSVD-based representation can handle flexible query structure consisting of an arbitrary number of objects and cameras. Simulation results are finally used to illustrate the superior performance of the proposed approach to multiple trajectory indexing and retrieval from multi-camera systems compared to the use of a single camera.