Evaluating local features for day-night matching

Hao Zhou, Torsten Sattler, David Jacobs

Abstract: This paper evaluates the performance of local features in the presence of large illumination changes that occur between day and night. Through our evaluation, we find that repeatability of detected features, as a de facto standard measure, is not sufficient in evaluating the performance of feature detectors; we must also consider the distinctiveness of the features. Moreover, we find that feature detectors are severely affected by illumination changes between day and night and that there is great potential to improve both feature detectors and descriptors.