Evaluating local features for day-night matching

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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.

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Zhou, H., Sattler, T., & Jacobs, D. W. (2016). Evaluating local features for day-night matching. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9915 LNCS, pp. 724–736). Springer Verlag. https://doi.org/10.1007/978-3-319-49409-8_60

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