Design and implementation of a compressive infrared sampling for motion acquisition

Tong Liu,Jun Liu

doi:10.1186/1687-6180-2014-20

Tong Liu, Jun Liu

Open Access

https://doi.org/10.1186/1687-6180-2014-20

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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.

Highlights

How to effectively acquire the human motion information is of key importance for analyzing and interpreting behavior
For the collection of the reference set, we randomly select half of the samples from each motion set as the template samples, and the remaining samples are used for test and analysis
6 Conclusions A compressive sampling-based pyroelectric infrared (PIR) sensor array for human motion sensing has been developed and evaluated in this article

Summary

Introduction

How to effectively acquire the human motion information is of key importance for analyzing and interpreting behavior. Wearable sensors and isomorphic vision sensors are the most used sensing methods for motion acquisition. The wearable sensor-based sensing method is able to directly obtain the motion information of specific limbs or joints. It can form the low-dimensional sensor outputbased feature representation [1]. The wearable sensor belongs to the intrusive sensing method. It needs the observed person to wear or wrap the sensor on the body, so the feeling of comfort will be affected

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