Body shape-based biometric recognition using millimeter wave images

The use of MMW images has been proposed recently in the biometric field aiming to overcome certain limitations when using images acquired at visible frequencies. In this paper, several body shape-based techniques are applied to model the silhouette of images of people acquired at 94 GHz. Three main approaches are presented: a baseline system based on the Euclidean distance, a dynamic programming method and a procedure using Shape Contexts descriptors. Results show that the dynamic time warping algorithm achieves the best results regarding the system performance (around 1.3% EER) and the computation cost. Results achieved here are also compared to previous works based on the extraction of geometric measures between several key points of the body contour. An average relative improvement of 33% EER is achieved for the work reported here.