Motion Tracking Based on Boolean Compressive Infrared Sampling

Abstract

This paper concerns the issue of motion tracking with Bayesian filtering driven by boolean compressive infrared sampling. In particular, this paper proposes an implementation of boolean compressive infrared sampling modality, and a measurement transformation method which maps the presence state recovered from boolean compressive infrared sampling into functional measurement for Bayesian filtering with a functional vector quantizer. Simulation studies are reported to validate the proposed transformation method in motion tracking.