homework 4

homework 4 - Introduction to Computer Vision CSE 152,...

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Introduction to Computer Vision Name : CSE 152, Spring 2011 Student ID : David Kriegman E-Mail : Assignment #4 (Due date: 06/03/2011) Instructions Please comment all your Matlab code adequately Turn in a hard copy of your code and required results . Put your hard copy in the TA’s mail box (CSE Building, 2 nd floor) before 5pm on the due date. In addition, please email to [email protected] a copy of your code. If it is a single file, just send the .m file. If it is contained in multiple files, send a zip or tar file. In the subject line, please put the string: “CSE152 Assignment 4”. The Yale face database We will have a look at some simple techniques for object recognition. In particular, we will try to recognize faces. The face data that we will use is derived from the Yale Face Database - for more information, see http://vision.ucsd.edu/~leekc/ExtYaleDatabase/Yale%20Face%20Database.htm . The database consists of 5760 images of 10 individuals, each under nine poses and 64 different lighting conditions. The availability of such standardized databases is important for scientific research as they provide a common testing ground to test the efficiency of different algorithms. Figure 1: The Yale face database B. In this assignment, we will only use 640 images corresponding to a frontal orientation of the face. These faces are included in the file yaleBfaces.zip . You will find the faces divided into five different subsets. Subset 0 consists of images where the light source direction is almost frontal, so that almost all of the face is brightly illuminated. From subset 1 to 4, the light source is progressively moved toward the horizon, so that the effects of shadows increase and not all pixels are illuminated. Note : An image with size [M, N] can be represented as a vector of length M*N (vectorized image). The provided Matlab code getAmatrix.m can be used to read the input images from yaleBfaces dataset. If you call A = getAmatrix (i, j) , columns of the output matrix A are the vectorized images of person j in subset i .
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If you call A = getAmatrix (i, []) , columns of the output matrix A are the vectorized images of all persons in subset i . If you call
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This note was uploaded on 08/05/2011 for the course CSE 152 taught by Professor Staff during the Spring '08 term at UCSD.

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homework 4 - Introduction to Computer Vision CSE 152,...

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