Tensor-Based Multiple Object Trajectory Indexing and Retrieval

This paper presents novel tensor-based object trajectory modelling techniques for simultaneous representation of multiple objects motion trajectories in a content based indexing and retrieval framework. Three different tensor decomposition techniques-PARAFAC, HOSVD and Multiple-SVD-are explored to achieve this goal with the aim of using a minimum set of coefficients and data-dependant bases. These tensor decompositions have been applied to represent full as well as segmented trajectories. Our simulation results show that the PARAFAC-based representation provides higher compression ratio, superior precision-recall metrics, and smaller query processing time compared to the other tensor-based approaches.

• Type: Conference
• Year: 2006
• Where: ICMCS
• Authors: Xiang Ma, Faisal I. Bashir, Ashfaq A. Khokhar, Dan Schonfeld
• Keywords: ICMCS 2006, Objects Motion Trajectories, Tensor Decomposition Techniques-PARAFAC, Tensor Decompositions