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Visual Place Recognition (VPR) has seen significant advances at the frontiersof matching performance and computational superiority over the past few years.However, these evaluations are performed for ground-based mobile platforms andcannot be generalized to aerial platforms. The degree of viewpoint variationexperienced by aerial robots is complex, with their processing power andon-board memory limited by payload size and battery ratings. Therefore, in thispaper, we collect $8$ state-of-the-art VPR techniques that have been previouslyevaluated for ground-based platforms and compare them on $2$ recently proposedaerial place recognition datasets with three prime focuses: a) Matchingperformance b) Processing power consumption c) Projected memory requirements.This gives a birds-eye view of the applicability of contemporary VPR researchto aerial robotics and lays down the the nature of challenges for aerial-VPR.

Are State-of-the-art Visual Place Recognition Techniques any Good for Aerial Robotics?