Dense Planar SLAM

Experimental AR computer vision project by Renato Salas-Moreno utilizes an RGB-D sensor and Oculus Rift to detect flat areas within a space to add digital content … such as placing a Facebook wall onto your living room wall – video embedded below:

We present an efficient new real-time approach which densely maps an environment using bounded planes and surfels extracted from depth images (like those produced by RGB-D sensors or dense multi-view stereo reconstruction). Our method offers the every-pixel descriptive power of the latest dense SLAM approaches, but takes advantage directly of the planarity of many parts of real-world scenes via a data-driven process to directly regularize planar regions and represent their accurate extent efficiently using an occupancy approach with on-line compression. Large areas can be mapped efficiently and with useful semantic planar structure which enables intuitive and useful AR applications such as using any wall or other planar surface in a scene to display a user’s content.

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