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131	CMSC 426 Problem Set 1 Due: Tuesday, February 18, 2003, 11:00, at the start of class. Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2003-02-04 17:14:26 Mathematics Cartography Geodesy Infographics Map projection Perspective Pinhole camera model Projection Imaging Perspective projection Functions and mappings Geometry
132	Problem Set 6 CMSC 426 Assigned April 8, 2010 Due April 22, 2010 Mosaics The goal of this problem set is to write code to form a mosaic of two images. We begin Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2010-04-08 17:25:01 Geometry Image processing RANSAC Affine transformation JPEG Scale-invariant feature transform 3D single object recognition Computer vision Statistics Vision
133	Problem Set 3 CMSC 427 Assigned October 23, 2007, Due November 6, 2007 Introduction: This problem set will focus on writing a program to morph one image into another. You will implement the approach described in: “Feat Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2007-10-23 13:16:08 Multivariate interpolation Interpolation Digital typography Spatial anti-aliasing Trigonometric functions Inverse function Bicubic interpolation Function Linear interpolation Mathematics Mathematical analysis Image processing
134	Problem Set 5 CMSC 426 Assigned April[removed]Due April 8, 2010 Blob Detection This problem set deals with some of the key components needed to perform blob Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2010-03-31 20:43:52 Vision Signal processing Blob detection Gaussian filter Difference of Gaussians Smoothing Convolution Scale-invariant feature transform Scale space implementation Image processing Computer vision Imaging
135	Problem Set 2 CMSC 426 Assigned: Feb. 5, 2004 Due: Feb. 12, 2004 In this problem you will need to write some code to rotate and translate 3D points, and to project them into a 2D image. You will be provided with three Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2004-02-04 21:37:32 Elementary mathematics Transformation MATLAB Numerical linear algebra Cartesian coordinate system Function Translation Subroutine Mathematics Software Geometry
136	Statistics for Image Modeling CMSC 426 Motivation To do vision, we need to model the world. For example, in edge detection, we used a qualitative model based on generalities about geometry and objects, which told us that Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2005-09-27 09:40:18 Statistics Pixel Prior probability Bilinear interpolation Contextual image classification Image processing Computer graphics Visual arts
137	Practice Sheet for CMSC 828J Midterm Spring 2009 Topics covered 1. Template Matching o Distance Transform o Chamfer matching Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2009-03-04 09:34:32 Projective geometry Affine geometry Matrices Linear algebra Affine transformation Rotation matrix Homogeneous coordinates Thin plate spline Space Geometry Mathematics Transformation
138	Correlation and Convolution Class Notes for CMSC 426, Fall 2005 David Jacobs Introduction Correlation and Convolution are basic operations that we will perform to extract Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2005-09-01 10:13:55 Signal processing Correlation and dependence Filter Pixel Gaussian filter Linear filter Image processing Mathematics Computer graphics
139	Problem Set 7 CMSC 426 Assigned Tuesday April 27, Due Tuesday, May[removed]Stereo Correspondence. For this problem set you will solve the stereo correspondence problem using dynamic programming, as described in class. The Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2010-04-27 10:05:44 Vision Pixel Template matching Contextual image classification Image processing Computer graphics Imaging
140	Practice Problems for Quiz 2 CMSC 426 Texture: For each pair of the following 1D textures, indicate whether we can distinguish between them using 1) the histogram of the image; 2) a Markov model in which each pixel depen Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2004-04-14 22:39:22 Rotation matrix Line Cartesian coordinate system Geometry Mathematics Analytic geometry

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