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2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2010)
San Francisco, CA, USA
June 13, 2010 to June 18, 2010
ISBN: 978-1-4244-6984-0
pp: 1141-1148
Jennifer Dolson , Dept. of Computer Science, Stanford University
Jongmin Baek , Dept. of Computer Science, Stanford University
Christian Plagemann , Dept. of Computer Science, Stanford University
Sebastian Thrun , Dept. of Computer Science, Stanford University
ABSTRACT
We present a flexible method for fusing information from optical and range sensors based on an accelerated high-dimensional filtering approach. Our system takes as input a sequence of monocular camera images as well as a stream of sparse range measurements as obtained from a laser or other sensor system. In contrast with existing approaches, we do not assume that the depth and color data streams have the same data rates or that the observed scene is fully static. Our method produces a dense, high-resolution depth map of the scene, automatically generating confidence values for every interpolated depth point. We describe how to integrate priors on object motion and appearance and how to achieve an efficient implementation using parallel processing hardware such as GPUs.
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CITATION

J. Baek, J. Dolson, C. Plagemann and S. Thrun, "Upsampling range data in dynamic environments," 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVPR), San Francisco, CA, USA, 2010, pp. 1141-1148.
doi:10.1109/CVPR.2010.5540086
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