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Abstract

Surface segmentation from RGB and depth images is described. In one example, a computer receives an image of a scene. The image has pixels which each have an associated color value and an associated depth value representing a distance between from an image sensor to a surface in the scene. The computer uses the depth values to derive a set of three-dimensional planes present within the scene. A cost function is used to determine whether each pixel belongs to one of the planes, and the image elements are labeled accordingly. The cost function has terms dependent on the depth value of a pixel, and the color values of the pixels and at least one neighboring pixel. In various examples, the planes can be extended until they intersect to determine the extent of the scene, and pixels not belonging to a plane can be labeled as objects on the surfaces.

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