PPT-GPU-Efficient Recursive Filtering and Summed-Area Tables

Author : giovanna-bartolotta | Published Date : 2017-06-02

D Nehab 1 A Maximo 1 R S Lima 2 H Hoppe 3 1 IMPA 2 Digitok 3 Microsoft Research Linear shiftinvariant filters But use feedback from earlier outputs

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GPU-Efficient Recursive Filtering and Summed-Area Tables: Transcript

D Nehab 1 A Maximo 1 R S Lima 2 H Hoppe 3 1 IMPA 2 Digitok 3 Microsoft Research Linear shiftinvariant filters But use feedback from earlier outputs. The recursive average is a very efficient way to obtain a time-weighted average by low-pass filtering the signal.. y[n] = (1-a)y[n-1] + ax[n]. Consider the output for a step input if a = 0.632. Output initialized to 0. F01943024. Reference. Yang, . Qingxiong. . "Recursive bilateral filtering." . ECCV . 2012. .. Deriche. , . Rachid. . "Recursively . implementating. the Gaussian and its derivatives." . ICIP 1993.. 2. Summed GDC 2005: Dynamic Glossy Environment Reflections Overview OverviewPresenting work started by Justin Hensley, Ph.D. student at UNC and a 2004 ATI Fellowship recipientSummed-area tablesUse for What are Summed Area Tables (SATs)?•integrated texture representation•Invented by Frank Crow, 1984•Each texelis the sum of all texelsbelow and to the left of it•Allows rapid box fi D. Nehab. 1. A. Maximo. 1. R. S. Lima. 2. H. Hoppe. 3. 1. IMPA . 2. Digitok. . . 3. Microsoft Research. Linear, shift-invariant filters. But use feedback from earlier outputs. D. Nehab. 1. A. Maximo. 1. R. S. Lima. 2. H. Hoppe. 3. 1. IMPA . 2. Digitok. . . 3. Microsoft Research. Linear, shift-invariant filters. But use feedback from earlier outputs. Recursion. Maureen Psaila-Dombrowski. Recursion . What is Recursion?. It is a concept/method used in computer science and mathematics. Recursive problem: The problem can be described as a reduced or smaller form of the same problem. Jeremiah van Oosten. Reinier. van . Oeveren. Introduction. Related Works. Prefix Sums and Scans. Recursive Filtering. Summed-Area Tables. Problem Definition. Parallelization Strategies. Baseline (Algorithm RT). Gernot Ziegler, NVIDIA Problem Task  Compute large number of area sums over input data (one - , two - or n - dimensional, integer or float).  Example of area sum request from 1D inpu Summed . Multi-Objective Ranks. Steven Bergen and Brian J. Ross. Brock University. Department of Computer Science. St. Catharines, Ontario, . Canada L2S 3A1. sb04qv@brocku.ca, . bross@brocku.ca. Outline. Self-reflection is the school of wisdom. Baltastar Gracián. 2. An organization chart. Every . structure for presenting data has an underlying data model. 3. Modeling a 1:1 relationship. 1:1 relationship is labeled. Josiah Manson and Scott Schaefer. Texas A&M University. Texture Parameterization. Texture Parameterization. Texture Parameterization. Texture Parameterization. MIP-Mapping. MIP-Mapping. MIP-Mapping. 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 . reflectivity . by . minimum. -delay. seismic trace decomposition. Milton J. . Porsani. Centro . de . Pesquisa. . em. . Geofísica. . e . Geologia. (CPPG/UFBA) and National. Institute of Science and Technology of Petroleum Geophysics (INCT-GP/CNPQ)..

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