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Bag of World Anchors for Instant Large-Scale Localization.
IEEE Transactions on Visualization and Computer Graphics 2023 October 3
In this work, we present a novel scene description to perform large-scale localization using only geometric constraints. Our work extends compact world anchors with a search data structure to efficiently perform localization and pose estimation of mobile augmented reality devices across multiple platforms (eg., hololens, ipad). The algorithm uses a bag-of-words approach to characterize distinct scenes (eg., rooms). Since the individual scene representations rely on compact geometric (rather than appearance-based) features, the resulting search structure is very lightweight and fast, lending itself to deployment on mobile devices. We present a set of experiments demonstrating the accuracy, performance and scalability of our novel localization method. In addition, we describe several use cases demonstrating how efficient cross-platform localization facilitates sharing of augmented reality experiences.
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