CS 436 Computer Vision Fundamentals Sohaib A Khan Room 215, [email protected]Office Hrs: M 10am-11am W 10am-11:am Th 3pm-4pm Course Status Elective for Senior/Graduate students Prerequisites: Strong programming background Mathematics Background Required Matrix Manipulation, Calculus Will be helpful, but not assumed Probability, Random Processes, Signal Processing…
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Course Status - Lahore University of Management Sciencessuraj.lums.edu.pk/~cs436a02/Lecture 1 handout.pdf · 2 Goals Basic Goal: Generate excitement about CV Introductory theory &
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Will be helpful, but not assumedProbability, Random Processes, Signal Processing…
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Goals
Basic Goal: Generate excitement about CV
Introductory theory & applications of CVDemonstration of simple exciting applicationsAbility to write programs to solve CV problemsExamples of CV SystemsIntro to some current research topics
Text
Computer VisionLinda G. Shapiro, George C. Stockman ISBN 0-13-030796-3 Prentice Hall, 2001Additional course notes and reading material will available through the course website.Programming Environment:
C/C++ and MATLAB
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Lectures
20 sessions, 100 minutes each1 in-class midterm, 1 final exam50 minutes each week for programming aspects of the courseNo grade for attendance
Grading
40% projects and programming assignments10% assignments/homework5% reading assignments
Graded through class participation/quizzes
20% mid-term25% final exam (non-comprehensive)
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Cheating/Plagiarism
Will not be tolerated…
Course Website
Tool to keep all reading links, additional information in one placeLecture notes and slides will be availablehttp://web.lums.edu.pk/~sohaib/cvf-fall02.htm
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What is Computer Vision
“The goal of Computer Vision is to make useful decisions about real physical objects and scenes based on sensed images”
ImageProcessing
Image IN Image OUT Computer Vision
Image IN
Symbolic Decision OUT
Computer Vision Area
Integration of several areasImage processingStatistical inferenceMachine intelligenceDecision theory…
Teaching methodologyCover some basic areasBreadth vs DepthShow lots of examples
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Module 1 (4 Sessions)
Introduction (1)Transformations and Imaging Geometry (3)
2D Transformations
Module 1 (4 Sessions)
Global Transformation ModelsAffine, Projective, Bilinear
From http://wearcam.org (Professor Steve Mann)
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Module 1 (4 Sessions)
3D Transformations
Camera ModelsCamera Calibration
Module 1 (4 Sessions)
WarpingApplying transformation to an imageCan be done for multiple images
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Module 2 (6 Sessions)
Basic Binary OperationsThresholding, Morphology, Region Properties, Moments, Connected Component Labeling
Images are essentially large matricesGray scale images are 2D matricesColor images have 3 layers (R, G, B)Each cell of the matrix represents a pixelEach pixel is quantized to a set of values, e.g. from 0-255 (1 Byte per pixel)
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PBM, PGM, PPM Format
Portable Bit Map FormatsSimple Image header in ASCIIImage data in either ASCII or Binary.PGM for Grayscale images.PPM for Color (RGB) images
Programming Assignment 0
Write Program to Read/Write BINARY .ppm & .pgm filesData will be available through course website
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Header
P2
# Created by IrfanView
128 128
255
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55 58 58 58 58 58 56 56 55 54 53 52
Magic Numbers for format identificationP2 - ASCII PGM P3 – ASCII PPMP5 – Binary PGMP6 – Binary PPM
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Tasks
Implement both in MATLAB and C/C++MATLAB Introduction