Computer Vision

Fall 2009


Please note - specifics of this schedule are subject to change.


Lecture slides are posted in the column named “Lectures”.


F&P = Forsyth & Ponce

S&S = Shapiro & Stockman [See Blackboard-> Course Documents]

T&V = Trucco & Verri [See Blackboard-> Course Documents]




Reading and references

Of related interest



Thurs 8/27






Pset 0: out 8/27, due 9/7

Pset 0 images

Part 2 code example solution

Solutions given in class on 9/15

Tues 9/1


Linear filters : F&P Chapter 7 sections 7.1, 7.2, 7.5, 7.6

[T&V Chapter 4]

[S&S Chapter 5.3]




Linear filters I







Thurs 9/3





Matlab intro


Matlab tutorial (guest lecture, Yong Jae Lee)


Tues 9/8


Linear filters, edges: F&P Ch 8

[S&S Chapter 3]


Linear filters 2

Pset 1: out 9/8, due 9/21

Pset 1 images

Seam carving page with video


Class results

Thurs 9/10



Edges: F&P Ch 8

Binary images: [S&S Chapter 3]


Edge detection and binary image analysis


Tues 9/15


Texture: F&P 9.1 and 9.3

A Statistical Approach to Texture Classification from Single Images, by Manik Varma and Andrew Zisserman, International Journal of Computer Vision, 2005.


When is Scene Identification Just Texture Recognition? by Laura Walker Renninger and Jitendra Malik, Vision Research, 2004.


Alyosha Efros’s Texture Synthesis page, with links to non-parametric sampling method and image quilting




Thurs 9/17

Grouping and Fitting

Segmentation: F&P Ch 14

k-means applet demo


Normalized Cuts and Image Segmentation, by Jianbo Shi and Jitendra Malik, PAMI 2000.


Ncuts Matlab code


Contour and Texture Analysis for Image Segmentation, by Malik et al. IJCV 2001.


Segmentation, clustering









Tues 9/22

Hough transform: F&P 15.1

[S&S pp. 304-310]

Excerpt from Ballard & Brown


Hough Transform demo

Hough, voting

Pset 2: out 9/22, due 10/5

Solutions given out in class 10/13

Thurs 9/24

Deformable contours:

[T&V p. 108-113]

[S&S p. 489-495]






Deformable contours

Tues 9/29

Background modeling and background subtraction


Read F&P 14.3, and


Stauffer & Grimson paper: Adaptive Background Mixture Models for Real-Time Tracking, CVPR 1999.



Background models (guest lecture by Birgi Tamersoy)

Thurs 10/1

Cameras and Multiple views

Fundamentals of image formation


Read F&P Chapter 1



Image formation

(guest lecture by Jaechul Kim)

Tues 10/6

Fitting and multiple views: alignment and image warping




Alignment, warping


Thurs 10/8

Robust fitting

Midterm review


F&P Section 15.5, 15.5.2





Tues 10/13

Midterm exam





Pset 3: out 10/13, due 10/27


Class results are posted here

Solutions given in class 11/3

Thurs 10/15

Midterm solutions given in class




Tues 10/20

Multiple views

Epipolar geometry and stereo vision

F&P sections 10.1.1-10.1.2

F&P sections 11.1-11.3

[T&V selected sections]


Epipolar geometry applet

Epipolar geometry, stereo


Thurs 10/22

Stereopsis, calibration



Video view interpolation, Zitnick et al.


Microphone arrays as generalized cameras for integrated audio visual processing, O’Donovan and Duraiswami


Body tracking, Demirdjian et al.


Fundamental matrix song


Stereopsis, calibration


Tues 10/27

Local invariant features: detection and description


Selected pages from:


Ch 3: Visual Recognition: Local Features: Detection and Description K. Grauman and B. Leibe [p. 23-39]


Local Invariant Feature Detectors: A Survey, T. Tuytelaars and K. Mikolajczyk, 2008.  [p. 178-188, 0.216-220, p. 254-255]





Distinctive Image Features from Scale-Invariant Keypoints, David Lowe, IJCV 2004.


SIFT demo software from David Lowe


Oxford group’s software for interest point detection and descriptors


VLFeat SIFT library from Andrea Vedaldi (C, and includes Matlab interfaces)

Invariant local features


Thurs 10/29


Image indexing and bag-of-words models


Ch 5: Visual Recognition: Visual Vocabularies.  K. Grauman and B. Leibe [p. 62-69]


Blackboard: bag of words model


Video Google: A Text Retrieval Approach to Object Matching in Videos, by J. Sivic and A. Zisserman, 2003.



Indexing, bag-of-words












Tues 11/3

Intro to recognition issues;


Model-based recognition with alignment and voting


F&P Sections 18.1, 18.3, 18.5


Pset3 solutions given out in class.


Object recognition from local scale-invariant features, David Lowe, 1999.

Intro to recognition problem, Alignment-based approach










Thurs 11/5

Part-based models and spatial cues from local features


Ch 7: Visual Recognition: Part-based Models.  K. Grauman and B. Leibe.  [p. 83-97]


Implicit shape model, Leibe et al., 2004.


Pyramid match kernel, Grauman & Darrell, 2005.


Spatial pyramid match kernel, Lazebnik et al. 2006.


LIBPMK : pyramid match toolkit


Part-based models and spatial cues for categories

Pset 4: out 11/5, due 11/24

Solutions given in class 12/1

Tues 11/10

(Face) detection via classification on appearance windows


F&P 22.1-22.2, 22.3.1-22.3.2


Rapid Object Detection using a Boosted Cascade of Simple Features, by P. Viola and M. Jones, 2001.


OpenCV Library, includes code for Viola-Jones face detector


Automated Visual Recognition of Individual African Penguins, by Burghardt et al., 2004.

Face detection

Thurs 11/12

Support vector machines for object classification


F&P 22.5


Histograms of Oriented Gradients for Human Detection, Dalal & Triggs, 2005.  Code


LIBSVM library for support vector machines


Learning Gender with Support Faces, Moghaddam & Yang, 2002.


Classification with support vector machines
















Tues 11/17

Shape matching

Face transformer, University of St. Andrews


Breaking a visual CAPTCHA, Mori & Malik


Matching with shape contexts, code, Belongie et al.


Shape matching

Thurs 11/19

Motion and Tracking

Motion and optical flow


T&V 8.3, 8.4



Optical flow





Tues 11/24

Tracking: linear dynamics


F&P 17.1-17.2.3, 17.3.1


Censusing bats, Infrared thermal video analysis of bats, Betke et al.


Pset 5: out 11/24, due 12/4*

Tues 12/1

Tracking wrapup

Tracking people by learning their appearance, Ramanan et al.


Condensation: Conditional Density Propagation for Visual Tracking, Isard and Blake; videos


Tracking, recap


Thurs 12/3

Exam review





12/14 Mon

Final exam 2-5 PM in JGB 2.218