Computer Vision
CS 554

Spring 2006

Department of Computer Engineering, Bilkent University


Instructor: Pinar Duygulu
Office :  EA 433
e-mail : duygulu[at]
Phone :  (312) 290 31 43
Office hours:  by appointment..
Course web page:
Textbook: Computer Vision - A modern Aproach  by David A. Forsyth & Jean Ponce, Prentice Hall, Ed. 1, 2002
Other textbooks:
Computer Vision by Dana Ballard and Chris Brown (available online)
Digital Image Processing by Rafael Gonzalez and Richard Woods
Computer Vision by Linda Shapiro and George Stockman
Related Material:
Also other complementary articles that will be made available
Previous course materials are avilable at
Time & Location: Mondays 11:40-13:00, Wednesdays 11:10-12:30, EA 502
Course Description Basic concepts in computational vision. Relation to human visual perception. The analysis and understanding of image and video data. Mathematical foundations, image formation and representation, segmentation, feature extraction, contour and region analysis, camera geometry and calibration, stereo, motion, 3-D reconstruction, object and scene recognition, object and people tracking, human activity recognition and inference.
Prerequisites:Knowledge of linear algebra and calculus, probability and statistics
Introduction,  Color and Light, Linear Filters, Texture,  Edge detection,  Interest Points, Cameras, Multi-view Geometry, Stereopsis,  Motion,  Segmentation,  Object recognition,  Face recognition,  Image and Vieo Databases
Assignments 50%
Paper Presentations 10%
Term Project 35%
Class Participation 5%





February 6



February 8


Binary Image Analysis

February 13


  • Topics
    • Applications of binary image analysis,Thresholding,Connected component analysis,Mathematical morphology,Region propoerties
  • Readings:
  • Links

Linear Filters

February 15, 20

(slides1, slides2)

  • Topics
    • Linear filters, convolution, smoothing, derivatives, Fourier transform, sampling and aliazing, gaussian pyramids
  • Readings
    • Chapter 7 from Forsyth&Ponce
    • Notes on masks, by Shapiro & Stockman
    • Computer vision for interactive computer graphics,W. T. Freeman, D. Anderson, P. Beardsley, C. Dodge, H. Kage, K. Kyuma, Y. Miyake, M. Roth, K. Tanaka, C. Weissman, W. Yerazunis,  in IEEE Computer Graphics and Applications, volume 18, number 3, May--June, pp. 42-53, 1998.
  • Links

Edge Detection

February 22


  • Topics
    • Derivatives, Edge detection, Hough Transform 
  • Readings
    • Chapter 8 from Forsyth&Ponce
    • A Computational Approach to Edge Detection, J. Canny, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 8, No. 6, Nov 1986.
    • Chapter 4 from Olivier Faugeras' book: Three-Dimensional Computer Vision, MIT Press, 1993
  • Links

Interest Points

February 27


  • Topics
    • Harris Detector, Local invariant points, SIFT descriptors


March 1

  • Topics
    • Texture analysis and synthesis 


March 6

  • Topics
    • Radiometry, measuring light
  • Readings:
    • Chapter 4 from Forsyth&Ponce


March 8



March 13


Camera Calibration

March 15


Multi view Geometry

March 20


  • Topics
    • Epipolar geometry


March 22

  • Topics
    • Stereopsis, Matching, Reconstruction 
  • Readings
    • Chapter 11 from Forsyth&Ponce
Spring Break
March 27, 29


April 3


  • Topics
    • Optical flow, structure from motion, Tracking
  • Readings


April 5



April 10,12


  • Topics
    • Segmentation, Grouping, Fitting


April 17


  • Topics
    • Model based and template matching based methods for recognition

Image and Video Databases

April 19


  • Topics
    • Retrieval, browsing and other novel applications on large datasests

Student Presentations

April 24

by Fahri Yaras, N. Ramanathan and R. Chellappa, Face Verification across Age Progression ,  CVPR 2005 (slides)

by Erdem Ulusoy, Y. Sheikh and M. Shah, Bayesian Object Detection in Dynamic Scenes, CVPR 2005 (slides)

Student Presentations
April 26
by Ahmet Tolgay, Yang Cheng, Andrew Johnson and Larry Matthies, MER-DIMES: A Planetary Landing Application of Computer Vision, CVPR 2005 (slides)

by Barkin Basarankut,  Junhwan Kim and Fabio Pellacini, Jigsaw Image Mosaics (JIM), ACM SIGGRAPH 2002. (slides)

by Okan Clingiroglu, Antonio S. Micilotta, Eng-Jon Ong, and Richard Bowden, Real-time Upper Body Detection and 3D Pose Estimation in Monoscopic Images, ECCV 2006 (slides)

by Hakan Ari, Arnab Ghoshal, Pavel Ircing, Sanjeev Khudanpur, Hidden Markov models for automatic annotation and content-based retrieval of images and video, SIGIR 2005 (slides)

Student Presentations
May 1
by Ozge Cavus, Yi Li, Linda G. Shapiro, Jeff A. Bilmes, A Generative/Discriminative Learning Algorithm for Image Classification,  iccv, pp. 1605-1612, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 2, 2005. (slides)

by Mert Duatepe, David Lowe and Stephen Se, Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks, (slides)

by Caglar Arslan, Oren Boiman and Michal Irani, Detecting Irregularities in Images and in Video, ICCV 2005 (slides)

Student Presentations
May 3
by Cihan Kucukkececi, M. Brown and D. Lowe. Recognizing panoramas. In Ninth International Conference on Computer Vision (ICCV'03), pages 1218–1225, Nice, France, October 2003. (slides)

by Hayati Cam, F. Jurie and C. Schmid, Scale-invariant shape features for recognition of object categories, CVPR 2004 (slides)

by Aysen Tunca, T. Brox, A. Bruhn, N. Papenberg, and J. Weickert, High Accuracy Optical Flow Estimation Based on a Theory for Warping, Proc. 8th European Conference on Computer Vision, 2004 (slides)

Student Presentations
May 8
by Esra Ataer, Toni M. Rath and R. Manmatha, Word-image matching Using Dynamic Time Warping, CVPR 2003 (slides)

by Emel Kaya, S. Newsam, S. Bhagavathy, and B. S. Manjunath, "Object Localization Using Texture Motifs and Markov Random Fields," International Conference on Image Processing, Barcelona, Spain, Sep 14-17, 2003. (slides)

by Tolga Can, Zeeshan Rasheed and Mubarak Shah, Scene Detection in Holywood Movies and TV Shows, CVPR 2003 (slides)

Student Presentations
May 10
by Iskender Yakin, O Veksler, Stereo Correpondence by Dynamic Programming on a Tree, CVPR 2005 (slides)

by Metin Tekkalmaz, Seyoun Park; Xiaohu Guo; Hayong Shin; Hong Qin, "Shape and Appearance Repair for Incomplete Point Surfaces," Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on Computer Vision, vol.2, no.pp. 1260- 1267, 17-20 Oct. 2005 (slides)

by Rifat Aras, Chi-Wei Chu, Odest Chadwicke Jenkins, Maja J Matarié , Markerless Kinematic Model and Motion Capture from Volume Sequences , CVPR 2003. (slides)

Student Presentations
May 15
by Kerem Altun, A. Torralba, K. P. Murphy, W. T. Freeman, and M. A. Rubin, Context-based vision system for place and object recognition, IEEE Intl. Conference on Computer Vision (ICCV), Nice, France, October, 2003. (slides)

by Huseyin Ozgur Tan, Vittorio Ferrari, Tinne Tuytelaars, Luc Van Gool,  Object Detection by Contour Segment Newtworks,  ECCV 2006 (slides)

by Oguzcan OguzImplicit Mashes for Modeling and Reconstruction, S. Ilic, P. Fua, CVPR2003 (slides)

Project  Presentations
May 26

Techniques for Background Subtraction in Urban Traffic Videos (report | slides)
by Aysen Tunca and Cihan Kucukkececi
American Sign Language (ASL) Interpretation Using Hand Gesture Recognition  (report | slides)
by Caglar Arslan and Okan Cilingiroglu
Ottoman Transcription System (report | slides)
by Esra Ataer and Tolga Can
Map Building using Stereo Vision in Outdoor Environment (report | slides)
by Mert Duatepe and Kerem Altun
Motion Detection in Video Sequences Recorded by a Moving Camera (report | slides)
by Metin Tekkalmaz and  Huseyin Ozgur Tan
Building Detection for Content Based Image Retrieval (report | slides)
by Ozge Cavus, Emel Kaya and Hayati Cam
Vehicle Speed Estimation and License Plate Detection (report | slides)
by Rifat Aras, Barkin Basarankurt and Hasan Hakan Ari
3D Stereo Motion Tracking (report | slides)
by Erdem Ulusoy and Fahri Yaras
Stereo-vision based Obstacle Detection and Swerving (report | slides)
by Iskender Yakin, Ahmet Tolgay and Oguzcan Oguz




Important notes about evaluation:

        There will be three reading assignments and three programming assignments      
        Late homeworks are not accepted     
        All programming assignments are due midnight and will be sent by e-mail
            In your e-mail use the following format in the title
            CS554 - Programming assignment #
            Your programming assignmenments should be sent as a tar ball in the following format
        All reading assignments are due before the lecture hours and will be given to the instructor as printed out
            Reading assignments will be summary of the given paper. It should be about one page,
            and you should explain the main contributions and the important points of the proposed
            methods in your own words. Do not include any figures or formulas. Do not write the values
            of parameters or thresholds unless they are very important. Assume that you are submitting
            one or two pages summary of your paper to a conference.

    The project may be
        An original implementation of a new or published idea,
        A detailed emprical evaluation and comparison of the existing implementations of two or more methods,     
    You will work in groups of two or three
    You are required to write a proposal, progress report, final report, and do a demonstration and a presentation 
        Project proposal will be a short description of the problem you would like to tackle, objective of the study,
         proposed algorithms, hardware/software tools and data that you plan to utilize, and evaluation strategies
        that you plan to use. Also provide a short list of related references.
        Progress report will describe your progress in the project and your plans for the rest of the semester
        Final report will be a well-written report which provides proper motivation for the task, proper citation
        and discussion of related literature, proper explanation of the details of the approach and implementation
        strategies, proper performance evaluation, and detailed discussion of the results. You should highlight
        your contributions and conclusions.
            Final report guidelines:
            Follow IEEE two-column format as shown in the example and the format definition table and glossary.
            The page limit is 6 pages.
            The report should not have any page numbers, headers or footers.
            You can use IEEE's LaTeX template or Word template. (LaTeX users: Be sure to use the template's conference mode.)
            PDF submission is recommended.
will be in the form of poster session and each team will show their contributions on a poster
        which will fit to a board of approximately 1m X 1m

    Your presentations will be evaluated according to the following criteria. Please, consider them in preparing your presentations:
        Understanding of the topic - how confident are you with the paper that you present
        Review of the related work - not just mentioning but by reading some of them to understand and relate to your paper
        Giving an overview of the paper -  the main contributions of the paper, and an overview of the approach
        Explaining the details - understanding and explaining the formulas and methods given in the paper
        Presentation - in general how well you are prepared to give the talk
        Use of visual material when available