Visual place recognition for aerial robotics: exploring accuracy-computation trade-off for local image descriptors

Ferrarini, Bruno, Waheed, Maria, Waheed, Sania, Ehsan, Shoaib, Milford, Michael and McDonald-Maier, Klaus D. (2019) Visual place recognition for aerial robotics: exploring accuracy-computation trade-off for local image descriptors. In 2019 NASA/ESA Conference on Adaptive Hardware and Systems (AHS). IEEE. pp. 103-108 . (doi:10.1109/AHS.2019.00011).

Abstract

Visual Place Recognition (VPR) is a fundamental yet challenging task for small Unmanned Aerial Vehicle (UAV). The core reasons are the extreme viewpoint changes, and limited computational power onboard a UAV which restricts the applicability of robust but computation intensive state-ofthe-art VPR methods. In this context, a viable approach is to use local image descriptors for performing VPR as these can be computed relatively efficiently without the need of any special hardware, such as a GPU. However, the choice of a local feature descriptor is not trivial and calls for a detailed investigation as there is a trade-off between VPR accuracy and the required computational effort. To fill this research gap, this paper examines the performance of several state-of-the-art local feature descriptors, both from accuracy and computational perspectives, specifically for VPR application utilizing standard aerial datasets. The presented results confirm that a trade-off between accuracy and computational effort is inevitable while executing VPR on resource-constrained hardware.

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Contributors

Author: Shoaib Ehsan

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