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Robust Camera Tracking by Combining Color and Depth Measurements

Erik Bylow ; Carl Olsson ; Fredrik Kahl (Institutionen för signaler och system, Bildanalys och datorseende)
International Conference on Pattern Recognition (2014)
[Konferensbidrag, refereegranskat]

One of the major research areas in computer vision is scene reconstruction from image streams. The advent of RGB-D cameras, such as the Microsoft Kinect, has lead to new possibilities for performing accurate and dense 3D reconstruction. There are already well-working algorithms to acquire 3D models from depth sensors, both for large and small scale scenes. However, these methods often break down when the scene geometry is not so informative, for example, in the case of planar surfaces. Similarly, standard image-based methods fail for texture-less scenes. We combine both color and depth measurements from an RGB-D sensor to simultaneously reconstruct both the camera motion and the scene geometry in a robust manner. Experiments on real data show that we can accurately reconstruct large-scale 3D scenes despite many planar surfaces.

Denna post skapades 2015-01-08. Senast ändrad 2016-05-24.
CPL Pubid: 210207


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Institutioner (Chalmers)

Institutionen för signaler och system, Bildanalys och datorseende (2013-2017)


Datorseende och robotik (autonoma system)
Medicinsk bildbehandling

Chalmers infrastruktur