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A new descriptor for multiple 3D motion trajectories recognition

Zhanpeng Shao, Youfu Li

发表年份
2013
引用次数
23

摘要

Motion trajectory gives a meaningful and informative clue in characterizing the motions of human, robots or moving objects. Hence, the descriptor for motion trajectory plays an importance role in motion recognition for many robotic tasks. However, an effective and compact descriptor for multiple 3D motion trajectories under complicated situation is lacking. In this paper, we propose a novel invariant descriptor for multiple motion trajectories based on the kinematic relation among multiple moving parts. There are two kinds of kinematic relation among multiple trajectories: articulated and independent trajectories. Spherical coordinate system is introduced to get a uniform and compact representation for both kinds of trajectories, where the relative trajectory concept are firstly defined based on orientation and distance changes in favor of acquiring relative movement features of each child trajectory with respect to the root trajectory. Then, by incorporating both the differential invariants of root trajectory and orientation, distance variations of each relative trajectory respectively, the new descriptor is constructed. Finally, effectiveness and robustness of our proposed new descriptor for multiple trajectories under complex circumstance are validated by the conducted two experiments for sign language and human action recognition.

关键词

TrajectoryKinematicsArtificial intelligenceMotion (physics)Computer visionRobustness (evolution)Computer scienceOrientation (vector space)MathematicsInvariant (physics)

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