Memorable Maps: A Framework for Re-defining Places in Visual Place Recognition
A novel cognition-inspired, agnostic framework is proposed for building maps in mobile robotics that are efficient in terms of image matching/retrieval for solving Visual Place Recognition (VPR) problem. A dataset, 'ESSEX3IN1', is also presented to demonstrate the significantly enhanced performance of state-of-the-art VPR techniques when combined with the proposed framework.
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