Abstract
With the spread of wearable and mobile devices, the request for interactive augmented reality applications is in constant growth. Among the different possibilities, we focus on the cultural heritage domain where a key step in the development applications for augmented cultural experiences is to obtain a precise localization of the user, i.e. the 6 degree-of-freedom of the camera acquiring the images used by the application. Current state of the art perform this task by extracting local descriptors from a query and exhaustively matching them to a sparse 3D model of the environment. While this procedure obtains good localization performance, due to the vast search space involved in the retrieval of 2D-3D correspondences this is often not feasible in real-time and interactive environments. In this paper we hence propose to perform descriptor quantization to reduce the search space and employ multiple KD-Trees combined with a principal component analysis dimensionality reduction to enable an efficient search. We experimentally show that our solution can halve the computational requirements of the correspondence search with regard to the state of the art while maintaining similar accuracy levels.
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Acknowledgments
This work was partially supported by the Fondazione Cassa di Risparmio di Modena project: “Vision for Augmented Experience” and the PON R&C project DICET-INMOTO (Cod. PON04a2 D).
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Gasparini, R., Alletto, S., Serra, G., Cucchiara, R. (2016). Optimizing Image Registration for Interactive Applications. In: De Paolis, L., Mongelli, A. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2016. Lecture Notes in Computer Science(), vol 9768. Springer, Cham. https://doi.org/10.1007/978-3-319-40621-3_36
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