Abstract
The study presents the comparison of detection and recognition of concealed objects covered with various types of clothing by using passive imagers operating in a terahertz (THz) range at 1.2 mm (250 GHz) and a mid-wavelength infrared (MWIR) at 3–6 μm (50–100 THz). During this study, large dataset of images presenting various items covered with various types of clothing has been collected. The detection and classification algorithms aimed to operate robustly at high processing speed across these two spectrums. Properties of both spectrums, theoretical limitations, performance of imagers and physical properties of fabrics in both spectral domains are described. The paper presents a comparison of two deep learning–based processing methods. The comparison of the original results of various experiments for the two spectrums is presented.
Real-Time Object Detection and Recognition on Low-Compute Humanoid Robots using Deep Learning
