Design and implementation of a compressive infrared sampling for motion acquisition

Abstract

This article proposes a compressive infrared sampling method in pursuit of the acquisition and processing of human motion simultaneously. The spatial-temporal changes caused by the movements of the human body are intrinsical clues for determining the semantics of motion, while the movements of short-term changes can be considered as a sparse distribution compared with the sensing region. Several pyroelectric infrared (PIR) sensors with pseudo-random-coded Fresnel lenses are introduced to acquire and compress motion information synchronously. The compressive PIR array has the ability to record the changes in the thermal radiation field caused by movements and encode the motion information into low-dimensional sensory outputs directly. Therefore, the problem of recognizing a high-dimensional image sequence is cast as a low-dimensional sequence recognition process. A database involving various kinds of motion played by several people is built. Hausdorff distance-based template matching is employed for motion recognition. Experimental studies are conducted to validate the proposed method. © 2014 Liu and Liu; licensee Springer.