A comparison of feature descriptors using monocular thermal camera images

This study investigates the rotational invariance of various image features extracted from monocular thermal and photo camera images that can be used for robot navigation. In addition to the conventional SIFT, SURF, ORB, AKAZE, and BRIEF image features, a new non-Gaussian binary feature descriptor is introduced using Levy-Laplace probability density functions. The rotational, viewpoint and noise invariance of all features are compared.