Результаты поиска по 'point cloud registration':
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  1. 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, v. 15, no. 3, pp. 657-674

    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.

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