Fang Jian-Shuen, Hao Qi, Brady David J, Shankar Mohan, Guenther Bob D, Pitsianis Nikos P, Hsu Ken Y
Opt Express. 2006 Jan 23;14(2):609-24. doi: 10.1364/opex.14.000609.
This paper presents a design and development of a low power consumption, and low cost, human identification system using a pyroelectric infrared (PIR) sensor whose visibility is modulated by a Fresnel lens array. The optimal element number of the lens array for the identification system was investigated and the experimental results suggest that the lens array with more elements can yield a better performance in terms of identification and false alarm rates. The other parameters of the system configuration such as the height of sensor location and sensor-to-object distance were also studied to improve spectral distinctions among sensory data of human objects. The identification process consists of two parts: training and testing. For the data training, we employed a principal components regression (PCR) method to cluster data with respect to different registered objects at different speed levels. The feature data of different objects walking along the same path in training yet at random speeds are then tested against the pre-trained clusters to decide whether the target is registered, and which member of the registered group it is.
本文介绍了一种利用热释电红外（PIR）传感器设计并开发的低功耗、低成本人体识别系统，该传感器的可见度由菲涅耳透镜阵列调制。研究了用于识别系统的透镜阵列的最佳元件数量，实验结果表明，元件数量更多的透镜阵列在识别率和误报率方面能产生更好的性能。还研究了系统配置的其他参数，如传感器位置高度和传感器到物体的距离，以改善人体目标传感数据之间的光谱差异。识别过程包括两个部分：训练和测试。对于数据训练，我们采用主成分回归（PCR）方法，以不同速度水平对不同注册对象的数据进行聚类。然后，将不同对象在训练中沿同一路径以随机速度行走的特征数据与预先训练的聚类进行测试，以确定目标是否已注册，以及它是注册组中的哪一个成员。
