In this study, we proposed novel designs for computational systems that use biometrics and non-conventional imaging approaches to capture thermal motion features of humans to achieve real-time path-dependent and path-independent gait for human identification. We have developed two pyroelectric infrared (PIR) feature-generating sensor systems. One system is analog, the other digital, and both are derived from the signals generated by humans crossing the detection areas. We successfully demonstrate that by selecting suitable sensor configurations and feature extraction/training algorithms, the sensor systems are capable of performing human identification.