Abstract
In this paper, an enhanced visual place recognition system is proposed aiming to improve the localization performance of a mobile platform. Our technique takes full advantage of the continuous input image stream in order to provide additional knowledge to the matching functionality. The well-established Bag-of-Visual-Words model is adapted into a hierarchical design that derives the visual information from the full entity of a natural scene into the description, while it additionally preserves the geometric structure of the explored world. Our approach is evaluated as part of a state-of-the-art Simultaneous-Localization-and-Mapping algorithm, and parallelization techniques are exploited utilizing every available hardware module in a low-power device. The implemented algorithm has been tested on several publicly available datasets offering consistently accurate localization results and preventing the majority of redundant computations that the additional geometrical verifications can induce.
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