F. Reyes Aviles ,  P. Fleck ,  D. SchmalstiegC. Arth (2023)

Bag of World Anchors for Instant Large-Scale Localization

communication medium



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 p erform l ocalization a nd p ose e stimation of mobile augmented reality devices across multiple platforms (e.g., HoloLens 2, iPad). The algorithm uses a bag-of-words approach to characterize distinct scenes (e.g., 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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research groups


Camera localization, Correspondence problem, 3D registration, Augmented Reality, Computer vision, Cross-platform, Collaborative, Structural modeling