  This paper presents a lightweight visual place recognition approach, capable
of achieving high performance with low computational cost, and feasible for
mobile robotics under significant viewpoint and appearance changes. Results on
several benchmark datasets confirm an average boost of 13% in accuracy, and 12x
average speedup relative to state-of-the-art methods.
