Background subtraction - PDFSEARCH.IO - Document Search Engine

Background subtraction
Results: 46

#	Item
31	Background Subtraction on Distributions Teresa Ko, Stefano Soatto, and Deborah Estrin Vision Lab Computer Science Department University of California, Los Angeles 405 Hilgard Avenue, Los Angeles – CA 90095 Add to Reading List Source URL: vision.ucla.edu Language: English - Date: 2008-08-28 23:50:23 Segmentation Normal distribution Mixture model Pixel Image processing Statistics Probability
32	Compressive Sensing for Background Subtraction Volkan Cevher1 , Aswin Sankaranarayanan2, Marco F. Duarte1 , Dikpal Reddy2 , Richard G. Baraniuk1 , and Rama Chellappa2 1 2 Add to Reading List Source URL: www.ece.rice.edu Language: English - Date: 2009-12-09 15:26:34 Information theory Compressed sensing Linear algebra Regression analysis Signal processing Basis pursuit denoising Function Sparse approximation JPEG Mathematics Mathematical optimization Statistics
33	O. BARNICH and M. VAN D ROOGENBROECK. ViBe : A universal background subtraction algorithm for video sequences. IEEE Transactions on Image Processing, 20(6) :[removed], June[removed]doi :[removed]TIP[removed]ViBe: A Add to Reading List Source URL: orbi.ulg.ac.be Language: English - Date: 2014-11-03 07:52:10 Signal processing Segmentation Thresholding Pixel Image noise Connected-component labeling Volume rendering Image processing Computer graphics Imaging
34	M. VAN D ROOGENBROECK, and O. BARNICH. ViBe: a disruptive method for background subtraction. In T. Bouwmans, F. Porikli, B. Hoferlin, and A. Vacavant, editors, Background Modeling and Foreground Detection for Video Surve Add to Reading List Source URL: orbi.ulg.ac.be Language: English - Date: 2014-11-20 11:47:30 Segmentation ViBe Image processing Computer vision Thresholding
35	Required background for first-year University Chemistry courses Mathematical skills: Write numbers in scientific notation; perform the operations of multiplication, division, subtraction, addition, taking square and cube Add to Reading List Source URL: www.umanitoba.ca Language: English - Date: 2014-11-20 16:51:09 Stoichiometry Chemical equation Chemical substance Molar mass Solubility Chemical compound Oxidation state Chemical formula IUPAC nomenclature of inorganic chemistry Chemistry Chemical nomenclature Chemical engineering
36	Warping Background Subtraction Teresa Ko Stefano Soatto Deborah Estrin University of California, Los Angeles, CA 90095 {tko, soatto, destrin}@cs.ucla.edu Add to Reading List Source URL: research.cens.ucla.edu Language: English - Date: 2010-08-09 12:40:37 Signal processing YUV Segmentation Gaussian blur Eigenface Normal distribution Pixel Image processing Computer graphics Imaging
37	Noname manuscript No. (will be inserted by the editor) Background Subtraction - Separating the Modeling and the Inference Manjunath Narayana · Allen Hanson · Add to Reading List Source URL: vis-www.cs.umass.edu Language: English - Date: 2013-10-13 21:03:15 Probability and statistics Computer graphics Pixel Segmentation Likelihood function Mixture model Image resolution Prior probability One-shot learning Image processing Statistics Bayesian statistics
38	NARAYANA, HANSON, LEARNED-MILLER: BMVC[removed]Improvements in Joint Domain-Range Modeling for Background Subtraction Add to Reading List Source URL: vis-www.cs.umass.edu Language: English - Date: 2012-12-27 22:42:49 Bayesian statistics Digital geometry Digital imaging Pixel Likelihood function Signal processing Statistics One-shot learning Image processing Computer graphics Digital photography
39	Problem Set 3 CMSC 426 Assigned Tuesday, Sept. 27, Due Tuesday, October 11 Background Subtraction 15 points For this problem, you are given a set of 100 images of background, I1, I2, … I100. and one test image, J. Thes Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2005-09-28 13:28:00 JPEG Evaluation Reference Template matching Image processing Graphics file formats Computing
40	Practice Midterm CMSC 426 The midterm will cover material up to and including background subtraction. Here are some topics it will be helpful to master for the midterm:  Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2010-03-18 10:16:21 Computer vision Computer graphics Gaussian function Histogram equalization Kernel density estimation Gaussian filter Histogram Edge detection Filter Image processing Statistics Non-parametric statistics