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1 June 2016 Real-time geometric scene estimation for RGBD images using a 3D box shape grammar
Andrew R. Willis, Kevin M. Brink
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Proceedings Volume 9867, Three-Dimensional Imaging, Visualization, and Display 2016; 986709 (2016) https://doi.org/10.1117/12.2225545
Event: SPIE Commercial + Scientific Sensing and Imaging, 2016, Baltimore, MD, United States
Abstract
This article describes a novel real-time algorithm for the purpose of extracting box-like structures from RGBD image data. In contrast to conventional approaches, the proposed algorithm includes two novel attributes: (1) it divides the geometric estimation procedure into subroutines having atomic incremental computational costs, and (2) it uses a generative “Block World” perceptual model that infers both concave and convex box elements from detection of primitive box substructures. The end result is an efficient geometry processing engine suitable for use in real-time embedded systems such as those on an UAVs where it is intended to be an integral component for robotic navigation and mapping applications.
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Andrew R. Willis and Kevin M. Brink "Real-time geometric scene estimation for RGBD images using a 3D box shape grammar", Proc. SPIE 9867, Three-Dimensional Imaging, Visualization, and Display 2016, 986709 (1 June 2016); https://doi.org/10.1117/12.2225545
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KEYWORDS
Data modeling
3D modeling
3D modeling
Image segmentation
3D image processing
3D image processing
Robotics
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