Path-dependent human identification using a pyroelectric infrared sensor and fresnel lens arrays.
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.
Duke Scholars
Altmetric Attention Stats
Dimensions Citation Stats
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Optics
- 5102 Atomic, molecular and optical physics
- 4009 Electronics, sensors and digital hardware
- 4006 Communications engineering
- 1005 Communications Technologies
- 0906 Electrical and Electronic Engineering
- 0205 Optical Physics
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Optics
- 5102 Atomic, molecular and optical physics
- 4009 Electronics, sensors and digital hardware
- 4006 Communications engineering
- 1005 Communications Technologies
- 0906 Electrical and Electronic Engineering
- 0205 Optical Physics