Hand motion tracking and trajectory matching for dynamic hand gesture recognition

摘要

Hand gesture recognition finds applications in areas like human computer interaction, machine vision, virtual reality and so on. In this article, we present a vision-based method for recognizing dynamic hand gestures via hand motion tracking and trajectory matching. A model-based approach based on HausdorfT distance is used for tracking hand motion thereby estimating the gesture trajectories. Dynamic Time Warping technique is employed for gesture trajectory time alignment and normalization. Recognition is done by extracting trajectory information like trajectory length, location, orientation and hand velocity from the estimated trajectory. Experimental results confirm the appropriateness of our proposed trajectory features and demonstrate that our proposed trajectory estimator and trajectory matching-based gesture classifier are efficient enough for use in Human Computer Interaction system.