Development and support of student technology startups by creating a successful startup community; assistance in providing favorable conditions from external partners for investment and development of ideas.
The university’s project-based activities are aimed at implementing grant-based and commercial projects, as well as at enhancing the availability of education in IT areas.
Analysis of mixed reality cross-device localization
algorithms based on point cloud registration
State of art approaches for localization and mapping is based on local features in images. Along with this, modern augmented and mixed reality devices allow building a mesh of the surrounding space. Using this mesh map, we can solve the problem of cross-device localization. This approach is independent of the type of feature descriptors and SLAM used onboard the AR / MR device. The mesh could be reduced to the points cloud, which takes only vertices. We propose the approach for co-localization of AR / MR devices using point clouds which do not depend on algorithms onboard the device. We analyzed various algorithms for registering point clouds and discuss of it limitation for the co-localization problem.