Computer Science 153: Computer Vision (Fall 2005)

MW, 1:15-2:30PM, TG 208

Instructor * Text * Overview * Links * Calendar * Honor Code

Instructor Information

Dr. Christine Alvarado
Office: Olin 1251
Email: alvarado@cs.hmc.edu
Office Hours: Tues 4:15-5:45, Wed 2:30-3:30, Fri 2-4 and by appointment (or whenever my door is open).

Text

Computer Vision: A Modern Approach
by Forsyth and Ponce

There will also be a number of supplemental readings

Course Overview

This course will focus on topics in and applications of level computer vision. While we will cover a number of areas of in computer vision, we will focus on high-level computer vision, examining techniques that enable the computer to perform automatic object segmentation and recognition in both visual and sketched images. Through a number of programming projects, we will examine techniques including binary and color image analysis, object segmentation, model representation, pattern classification, and sketch processing and recognition.

Links

Calendar

This calendar will be updated as the class progresses. I will try to post reading assignments at least a day or two in advance of the relevant lecture.

Date Lecture Reading Homework
Wed, Aug 31 Introduction Chapter 1 PS 1 Out
Mon, Sept 5 Light and Sources Chapter 4, 5.2
Wed, Sept 7 Binary Images and Filtering N/A PS 1 Due (midnight)
PS 2 out
Mon, Sept 12 Color, Reading a research paper Chapter 6
Wed, Sept 14 Segmentation by clustering, Filters Chapter 14.1-14.2, 14.4, 7.1-7.3,7.5
Mon, Sept 19 Research paper #1, Texture Contour and Texture Analysis
for Image Segmentation

Chapter 9.1-9.2
Paper review
Wed, Sept 21 Intro to Recognition
by Classification
Chapter 22.1 PS 2 Due on Friday
Mon, Sept 26 More Classification and PCA Chapter 22.2-22.4
Wed, Sept 28 More PCA PS 3 out
Mon, Oct 3 Paper presentation #2 Eigenfaces for Recognition
by Turk and Pentland [TP91]
Paper review #2 due
Wed, Oct 5 Line/Shape Fitting
via the Hough Transform
Chapter 15.1-15.3
Mon, Oct 10 More Line/Shape Fitting
Probabilistic Models
15.4-15.5
Wed, Oct 12 Probabilistic Fitting (cont) 15.4-15.5, Ch 16 (EM) PS 3 Due on Friday 10/14 by 5pm
Mon, Oct 17 No Class (Fall break)
Wed, Oct 19 EM (cont)
Paper presentation #3
Ch 16 (EM)
Contextual Priming for Object Detection
by A. Torralba
Paper review #3 due
Mon, Oct 24 NO CLASS
Wed, Oct 26 More Complex Model Fitting
Challenges of Sketch Understanding
Ch 18 (some material not in book) Project Proposal due on Friday 10/28 by 11:59pm
PS4 Out
Mon, Oct 31 Paper presentation #4 Combining geometry and domain knowledge to interpret hand-drawn diagrams by Gennari, Kara, Stahovich and Shimada Paper review due
Wed, Nov 2 Stroke Parsing [CD04], [S04], [SD04]
Mon, Nov 7 Camera Parameters and Calibration Ch 2, 3.1
Wed, Nov 9 Stereopsis Ch 10.1, 11 PS 4 Due on Friday 11/11 by 11:59pm
Mon, Nov 14 Model-Based Vision Ch 18
Wed, Nov 16 Model-Based Vision (cont) Ch 18 PS 4 Extension and redo of part 2 due Friday
Mon, Nov 21 Paper Presentation #5 "Utilizing Segmented MRI Data in Image-Guided Surgery" by Grimson et al. Paper review #5
Wed, Nov 16 Project Meetings

Additional Reading

[MBLS01] Jitendra Malik, Serge Belongie, Thomas Leung and Jianbo Shi. Contour and Texture Analysis for Image Segmentation. International Journal of Computer Vision 43(1). pp. 7-27.

[TP91] Matthew Turk and Alex Pentland. "Eigenfaces for Recognition." Journal of Cognitive Neuroscience, 3 (1). 1991.

[T03] Antonio Torralba. "Contextual Priming for Object Detection". International Journal of Computer Vision, 53 (2): 153-167.

[GKSS05] Leslie Gennari, Levent Burak Kara, Thomas F. Stahovich, and Kenji Shimada. Combining geometry and domain knowledge to interpret hand-drawn diagrams. Computers and Graphics 29 (4) 2005.

[CD05] Sonya Cates and Radall Davis, A New Approach to Early Sketch Processing. AAAI Symposium on Making Pen-Based Interfaces Intelligent and Natural. 2004.

[S05] Thomas F. Stahovich. Segmentation of Pen Strokes Using Pen Speed. AAAI Symposium on Making Pen-Based Interfaces Intelligent and Natural. 2004.

[SD05] Tevfik Metin Sezgin and Radall Davis, Scale-Space Feature Point Detection for Digital Ink. AAAI Symposium on Making Pen-Based Interfaces Intelligent and Natural. 2004.

[GEKLWK97] E. Grimson, G. Ettinger, T. Kapur, M. Leventon, W. Wells, R. Kikinis, "Utilizing Segmented MRI Data in Image-Guided Surgery", Int. J. Pattern Recognition & Artificial Intelligence, special issue on Processing, Analysis, and Understanding of Magnetic Resonance Images of the Human Brain, 11(8):1367-1397, 1997

Honor Code

Your work in this class should be in conformance with the Harvey Mudd honor code. For the problem sets, you may discuss problems with other students, but you should each write up/program your own solutions. Please list names of all people with whom you discussed problems in your writeup. For the project, you will be given the opportunity to work in teams of two or three students, but it is important that the work submitted be that only the students in the group, as well as the work of all of the students in the group. For the paper reviews, while you may discuss the papers, each student must write his or her own review.

If you have any question at all as to what is considered acceptable collaboration, please ask.