Analysis of mixed reality cross-device global localization algorithms based on point cloud registration

Osipov A.A., Ostanin M.A., Klimchik A.S.
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State-of-the-art localization and mapping approaches for augmented (AR) and mixed (MR) reality devices are based on the extraction of local features from the camera. Along with this, modern AR/MR devices allow you to build a three-dimensional mesh of the surrounding space. However, the existing methods do not solve the problem of global device co-localization due to the use of different methods for extracting computer vision features. Using a space map from a 3D mesh, we can solve the problem of collaborative global localization of AR/MR devices. This approach is independent of the type of feature descriptors and localisation and mapping algorithms used onboard the AR/MR device. The mesh can be reduced to a point cloud, which consists of only the vertices of the mesh. We propose an approach for collaborative localization of AR/MR devices using point clouds that are independent of algorithms onboard the device. We have analyzed various point cloud registration algorithms and discussed their limitations for the problem of global co-localization of AR/MR devices indoors.

Keywords: co-localization, augmented and mixed reality, point cloud registration
Citation in English: Osipov A.A., Ostanin M.A., Klimchik A.S. Analysis of mixed reality cross-device global localization algorithms based on point cloud registration // Computer Research and Modeling, 2023, vol. 15, no. 3, pp. 657-674
Citation in English: Osipov A.A., Ostanin M.A., Klimchik A.S. Analysis of mixed reality cross-device global localization algorithms based on point cloud registration // Computer Research and Modeling, 2023, vol. 15, no. 3, pp. 657-674
DOI: 10.20537/2076-7633-2023-15-3-657-674
URL: http://crm-en.ics.org.ru/journal/article/3337/
Creative Commons License This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License.

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