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GTC ON-DEMAND

Computer Vision
Presentation
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GPU-Accelerated 3D Surface Reconstruction Using Gaussian Mixture Sampling and Sparse Voxel Lists
Abstract:

As 3D depth sensors become smaller, cheaper, and more ubiquitous, it is becoming increasingly important to develop efficient and robust techniques to manage and process point cloud data. A common operation of particular importance is the ability to derive solid 3D geometry from unorganized sets of points. In this poster, we describe a parallel method to both process and compress 3D point data into a statistical parametric form in order to quickly construct a 3D triangle mesh using a modified form of the Marching Cubes algorithm.

 
Topics:
Computer Vision, Artificial Intelligence and Deep Learning
Type:
Poster
Event:
GTC Silicon Valley
Year:
2015
Session ID:
P5224
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