Environment mapping and other applications of world projections
IEEE Computer Graphics and Applications
A volumetric method for building complex models from range images
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
MLESAC: a new robust estimator with application to estimating image geometry
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
Range image segmentation based on randomized Hough transform
Pattern Recognition Letters
The Great Buddha Project: Digitally Archiving, Restoring, and Analyzing Cultural Heritage Objects
International Journal of Computer Vision
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust Methods for Geometric Primitive Recovery and Estimation From Range Images
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Range image segmentation using surface selection criterion
IEEE Transactions on Image Processing
People detection using color and depth images
MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
3D reconstruction of cultural heritages: Challenges and advances on precise mesh integration
Computer Vision and Image Understanding
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Separating data from objects of interest and background is a common procedure in range images applications. Most of the works presented in the literature use image segmentation, either automatic or supervised, to do that. We present a new method to automatically perform this separation without the need of using complex image segmentation techniques. In our approach, we consider that the object is always scanned over a supporting plane. Then, we assume that there is no information below the plane, and the object data is above it. By projecting all points into the supporting plane normal direction, the points on the plane would project at the same value, the points on the object would be spread with values larger than the plane, and there would be very few values below the plane value (due to noise). This allows us to quickly and reliably eliminate the background data from range images.