Computer Science and Engineering Department

CS485/685: Computer Vision (Spring 2012)

Meets: TR: 11:00am - 12:15pm (SEM 347)

Instructor: Dr. George Bebis

• Email: bebis@cse.unr.edu
• Phone: (775) 784-6463
• Office: 235 SEM
• Office Hours: TR 4:00 pm - 5:30 pm

Course Prerequisites

CS302 (Data Structures). Good programming skills and mathematical background are essential. Knowledge of Image Processing (CS474/674) is desired but not required. Credit hours: 3.0

Textbooks

No specific text is required for this class. We will be covering material from several different textbooks (see list below) and research papers. Lecture slides and reading material will be available from the course.s webpage.
• [Jain95] R. Jain et. al, Machine Vision McGraw Hill, 1995
• [Shah92] M. Shah, Fundamentals of Computer Vision, (available on-line).
• [Trucco98] Introductory Techniques for 3-D Computer Vision by Emanuele Trucco, Alessandro Verri, Prentice Hall, 1998.
  
• [Nalwa93] V. Nalwa, A Guided Tour of Computer Vision, Addison-Wesley, 1993.
• [Shapiro01] L. Shapiro and G. Stockman, Computer Vision Prentice Hall, 2001.
• [Sonka08] M. Sonka et. al, Image Processing, Analysis, and Machine Vision, Brooks/Cole Pub Co., 3rd edition, 2008.
• [Gonzalez09] R. Gonzalez and R. Woods Digital Image Processing, 3rd edition, Prentice Hall, 2008.
• [Szeliski10] R. Szeliski, Computer Vision: Algorithms and Applications, Springer-Verlag, 2011 (freely available on-line).
• D. Forsyth and Ponce, Computer Vision - A modern approach Prentice Hall, 2002.
• R. Haralick and L. Shapiro, Computer and Robot Vision (vol I and II)
• [OpenCV08] Learning OpenCV: Computer Vision with the OpenCV Library by Gary Bradski and Adrian Kaehler, O.Reilly Press, 2008.
  

Major CV Journals:

• IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)
• Computer Vision and Image Understanding (CVIU)
• International Journal of Computer Vision (IJCV)
• Image and Vision Computing (IVC)
• IEEE Transactions on Image Processing (TIP)
• Pattern Recognition (PR)
• Machine Vision and Applications (MVA)

• The image class: image.h and a simple implementation image.cpp
  
  
• C++ routine to read a PGM image: ReadImage.cpp
  
  
• C++ routine to read the header of a PGM image: ReadImageHeader.cpp
  
  
• C++ routine to write a PGM image: WriteImage.cpp
  
  
• Example: Threshold.cpp
  
• A makefile for compiling the example
  
• Try the code using this image: dimes.pgm
  
• Example output using threshold=128: th.pgm
  

Syllabus

• Spring 2012 syllabus

Exams

• Sample Midterm Exam


• Sample Final Exam

Lectures

• Course Overview

• Introduction to Computer Vision

• Image Formation and Representation Readings: 1 (from [Shapiro01]), 2 (from [Nalwa93]), and 3 (from [Gonzalez08])

• Image Filtering Readings: 1 (from [Gonzalez08]) and 2 (from [Jain95])

• Edge Detection Readings: 1 (from [Jain95]) and Chapter 2 (from [Shah92])

• Math Review
  • Vectors Readings: 1
  • Matrices Readings: 1
    
  • Singular Value Decomposition (SVD) Readings: 1 (from [Trucco98]) and 2
  • Linear Systems of Equations Readings: 1 (from [Trucco98]) and 2
    
  • Geometric Transformations Readings: 1

• Interest Point Detection Readings: 1, 2, Section 4.1.1 from [Szeliski10], and [Mikolajczyk04].
  [Schmid01] C. Schmid, R. Mohr, and C. Bauckhage,"Indexing based on scale invariant interest points", International Conference on Computer Vision, pp. 525-531, 2001 (Harris-Laplace detector).

  [Schmid00] C. Schmid, R. Mohr, and C. Bauckhage,"Evaluation of Interest Point Detectors", International Journal of Computer Vision 37(2), 151.172, 2000.

  [Mikolajczyk04] K. Mikolajczyk and C. Schmid,"Scale and Affine Invariant Interest Point Detectors", International Journal of Computer Vision, 60(1), pp. 63-86, 2004 (Harris-Laplace and Harris-Affine).

  [Tuytelaars08] T. Tuytelaars and K. Mikolajczyk,"Local Invariant Feature Detectors: A Survey", Computer Graphics and Vision, vol. 3, no. 3, pp. 177-280, 2008.

• Midterm Exam Review

• Interest Point Descriptors and Matching Readings: Sections 4.1.2 and 4.1.3 from [Szeliski10], and [Lowe04].
  [Mikolajczyk05] K. Mikolajczyk and C. Schmid,"A Performance Evaluation of Local Descriptors", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 10, pp. 1615-1630, 2005. (nice review and comparison of different local descriptors)

  [Lowe04] D. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints", International Journal of Computer Vision, 60(2):91-110, 2004.

• Object Recognition Readings: Sections 4.1.3 and 14.4.1 from [Szeliski10]
  [Wolfson97] H. Wolfson and I. Rigoutsos, Geometric Hashing: An Overview, IEEE Computational Science and Engineering, 1997.

  [Lowe04] D. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints", International Journal of Computer Vision, 60(2):91-110, 2004.

  [Gruska04] G. Csurka, C. Dance, L. Fan, J. Willamowski, C. Bray, Visual Categorization with Bags of Keypoints, European Conference on Computer Vision, Czech Republic, 2004.

• Face Recognition Using Eigenfaces Readings: 1 and Section 14.2.1 from [Szeliski10]
  [Turk91] M. Turk and A. Pentland, Face Recognition Using Eigenfaces, Computer Vision and Pattern Recognition Conference, 1991.

• Camera Parameters Readings: 1 (from [Nalwa93]) and 2 (from [Trucco98])

• Camera Calibration Readings: 1 (from [Trucco98])
  • Z. Zhang. "A flexible new technique for camera calibration", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 11, pp. 1330-1334, 2000.
• Stereo Vision Readings: 1 (from [Trucco98])
  • R. Hartley, "In Defense of the Eight-Point Algorithm", IEEE Transactions on Pattern Analysis and Machine Intelligence 19(6): 580-593, 1997.
• Final Exam Review
  
  

Homeworks

• Homework 1
• Homework 2 (click here for solutions)
• Homework 3 (click here for solutions)

Programming Assignments

• Image Database
  
• Instructions for Submitting Project Reports
  
  
• Prog. Assignment 1 (due on: 3/6/2012)
  
  Rect_128.dat
  
  
  
• Prog. Assignment 2 (due on 3/27/2012)
  svdcmp.c, svksb.c, solve_system.c, and Test.cpp; also, see makefile (chapter on SVD from Numerical Recipies)
  Face images, Facial features coordinates, and Fixed facial features coordinates
  
  H. Rowley, S. Baluja, and T. Kanade, "Neural Network-Based Face Detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 1, January, 1998, pp. 23-38 (see page 3).
  
  G. Bebis, S. Uthiram, and M. Georgiopoulos, "Face Detection and Verification Using Genetic Search", International Journal on Artificial Intelligence Tools, vol 9, no 2, pp. 225-246, 2000 (see pages 9-10).
  
  
  
• Prog. Assignment 3 (due on: 4/17/2012)
  
  FirstDerivativeGaussian.c
  Images to be used for testing: test.zip, boat.zip and graf.zip
  
  
  
• Prog. Assignment 4 (due on: 5/8/2012)
  
  Face images
  
  Phillips, J. and Moon, H. and Risvi, S. and Rauss, J., The FERET Evaluation Methodology for Face Recognition Algorithms", vol. 22, no. 10, pp. 1090-1104, 2000.
  
  The Face Recognition Homepage
  
  Eigen-decomposition example
  
  jacobi.c and jacobi.h
  
  

  Paper Presentations

  
  Oral Presentation Advice
  
  
• Andrea Frome and Jitendra Malik, "Object Recognition Using Locality-Sensitive Hashing of Shape Contexts", (by Ilias Apostolopoulos) powerpoint
  
  
• Eric Nowak and Fredric Jurie, "Learning Visual Similarity Measures for Comparing Never Seen Objects", (by Khoa Tran) powerpoint
  
  
• F. Schaffalitzky and A. Zisserman, "Multi-view matching for unordered image sets, or How do I organize my holiday snaps?", (by Abbas Roayaei) powerpoint