PPT-Efficient Sparse Voxel Octrees

Samuli Laine Tero Karras NVIDIA Research Bitmaps vs Vectors 2 Bitmap 2D image Vector 2D image Why Not Bitmaps in 3D 3 Bitmap 3D object Vector 3D object Voxel datasets often consist of volume data . Such matrices has several attractive properties they support algorithms with low computational complexity and make it easy to perform in cremental updates to signals We discuss applications to several areas including compressive sensing data stream From Theory to Practice . Dina . Katabi. O. . Abari. , E. . Adalsteinsson. , A. Adam, F. . adib. , . A. . Agarwal. , . O. C. . Andronesi. , . Arvind. , A. . Chandrakasan. , F. Durand, E. . Hamed. , H. . to Multiple Correspondence . Analysis. G. Saporta. 1. , . A. . . Bernard. 1,2. , . C. . . Guinot. 2,3. 1 . CNAM, Paris, France. 2 . CE.R.I.E.S., Neuilly sur Seine, France. 3 . Université. . François Rabelais. Richard Peng. M.I.T.. Joint work with Dan Spielman (Yale). Efficient Parallel Solvers for SDD Linear Systems. Richard Peng. M.I.T.. Work in progress with . Dehua. Cheng (USC),. Yu Cheng (USC), . Yintat. Full storage:. . 2-dimensional array.. (nrows*ncols) memory.. 31. 0. 53. 0. 59. 0. 41. 26. 0. 31. 41. 59. 26. 53. 1. 3. 2. 3. 1. Sparse storage:. . Compressed storage by columns . (CSC).. Three 1-dimensional arrays.. current voxel there is no need to intersect anyother objects as we have found the closest intersection.Ifno intersection is found in the current voxel or the object list is empty,wefollowthe ray into Recovery. . (. Using . Sparse. . Matrices). Piotr. . Indyk. MIT. Heavy Hitters. Also called frequent elements and elephants. Define. HH. p. φ. . (. x. ) = { . i. : |x. i. | ≥ . φ. ||. x||. p. Tianzhu . Zhang. 1,2. , . Adel Bibi. 1. , . Bernard Ghanem. 1. 1. 2. Circulant. Primal . Formulation. 3. Dual Formulation. Fourier Domain. Time . Domain. Here, the inverse Fourier transform is for each . to Multiple Correspondence . Analysis. G. Saporta. 1. , . A. . . Bernard. 1,2. , . C. . . Guinot. 2,3. 1 . CNAM, Paris, France. 2 . CE.R.I.E.S., Neuilly sur Seine, France. 3 . Université. . François Rabelais. Author: . Vikas. . Sindhwani. and . Amol. . Ghoting. Presenter: . Jinze. Li. Problem Introduction. we are given a collection of N data points or signals in a high-dimensional space R. D. : xi ∈ . Dina . Katabi. O. . Abari. , E. . Adalsteinsson. , A. Adam, F. . adib. , . A. . Agarwal. , . O. C. . Andronesi. , . Arvind. , A. . Chandrakasan. , F. Durand, E. . Hamed. , H. . Hassanieh. , P. . Indyk. Voxel. Database Structures on the GPU. Rama . Hoetzlein. , NVIDIA. High Performance Graphics 2016. Trinity College, Dublin. Sparse Volume Rendering. Meshes & Point Clouds. Binary . Voxels. Kampe. Octrees & Fractals. Contents. In today’s lecture we would like to continue on from the last day and look at some more modelling techniques. Octrees. Fractals. Octrees. Octrees are hierarchical tree structures used to represent solid objects. Parallelization of Sparse Coding & Dictionary Learning Univeristy of Colorado Denver Parallel Distributed System Fall 2016 Huynh Manh 11/15/2016 1 Contents Introduction to Sparse Coding Applications of Sparse Representation