On Integral Invariants for Effective 3-D Motion Trajectory Matching and Recognition

IEEE Transactions on Cybernetics
Zhanpeng Shao, Youfu Li

Abstract

Motion trajectories tracked from the motions of human, robots, and moving objects can provide an important clue for motion analysis, classification, and recognition. This paper defines some new integral invariants for a 3-D motion trajectory. Based on two typical kernel functions, we design two integral invariants, the distance and area integral invariants. The area integral invariants are estimated based on the blurred segment of noisy discrete curve to avoid the computation of high-order derivatives. Such integral invariants for a motion trajectory enjoy some desirable properties, such as computational locality, uniqueness of representation, and noise insensitivity. Moreover, our formulation allows the analysis of motion trajectories at a range of scales by varying the scale of kernel function. The features of motion trajectories can thus be perceived at multiscale levels in a coarse-to-fine manner. Finally, we define a distance function to measure the trajectory similarity to find similar trajectories. Through the experiments, we examine the robustness and effectiveness of the proposed integral invariants and find that they can capture the motion cues in trajectory matching and sign recognition satisfactorily.

References

Jan 12, 2005·IEEE Transactions on Pattern Analysis and Machine Intelligence·Erdem Bala, A Enis Cetin
Jun 24, 2005·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Dimitios Makris, Tim Ellis
Nov 16, 2005·IEEE Transactions on Pattern Analysis and Machine Intelligence·Greg MoriJitendra Malik
Sep 22, 2006·IEEE Transactions on Pattern Analysis and Machine Intelligence·Siddharth ManayStefano Soatto
Mar 23, 2013·IEEE Transactions on Pattern Analysis and Machine Intelligence·Weiming HuZhongfei Zhang
Sep 13, 2014·IEEE Transactions on Cybernetics·Maxime DevanneAlberto Del Bimbo
Sep 10, 2015·IEEE Transactions on Pattern Analysis and Machine Intelligence·Byung-Woo Hong, Stefano Soatto

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