DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
UNIVERSITY OF CALIFORNIA, SAN DIEGO
Students taking the course for four units should follow these project guidelines. Here is the feedback form for presentations.
Please read, reflect upon, and follow these presentation guidelines, kindly provided by Prof. Elkan. Immediately after your presentation, please email to sjb+cse252c@cs a copy of your slides. For ease of viewing, please make this copy be two slides per page in Adobe PDF.
The schedule of papers and presentations is below. Participants who have not chosen a paper yet should look at the list of suggested papers and contact the instructor.
If you want to change your presentation date, please arrange a swap with another student and notify the instructor at least two weeks in advance.
date 
presenter 
paper title 
author(s) 
discussion 
slides 
Sept. 26 
organizational meeting 




Oct. 1  Sameer Agarwal  A Generalization of Principal Component Analysis to the Exponential Family  Collins, Dasgupta and Schapire  
Oct. 3  Josh Wills  Combining topology and appearance for wide baseline matching  Tell & Carlsson  
Oct. 8  Satya Mallick  A global matching framework for stereo computation  Tao, Sawhney, and Kumar  
Oct. 10  Kristin Branson  A global geometric framework for nonlinear dimensionality reduction / Nonlinear dimensionality reduction by locally linear embedding  Tenenbaum, De Silva, and Langford / Roweis and Saul  
Oct. 15  Jongwoo Lim  Efficient region tracking with parametric models of geometry and illumination  Hager and Belhumeur  
Oct. 17  Andrew Rabinovich  The chromatic structure of natural scenes  Wachtler, Lee and Sejnowski  
Oct. 22  Serge Belongie  Feature Based Methods for Structure and Motion Estimation / All About Direct Methods  Torr and Zisserman / Irani and Anandan  
Oct. 24  Piotr Dollar  Order Structure, Correspondence, and Shape Based Categories  Carlsson  
Oct. 29  Bruno Olshausen  Sparse Coding of TimeVarying Natural Images (Note room & time change: INC Seminar, 12:00 Noon, CSB 003) 


Oct. 31  Satya Mallick  Geometric Camera Calibration  Forsyth and Ponce  
Nov. 5  no meeting 


Nov. 7  Kristin Branson  Direct methods for visual scene reconstruction  Szeliski and Kang  
Nov. 12  Ben Ochoa  Segmentation of Dynamic Scenes from the Multibody Fundamental Matrix (long version)  Vidal, Soatto, Ma and Sastry  
Nov. 14  Sameer Agarwal  Linear scalespace: I. Basic theory, II. Early visual operations  Lindeberg and ter Haar Romeny  
Nov. 19  Piotr Dollar  Recognition by Linear Combinations of Models  Ullman and Basri  
Nov. 21  Jongwoo Lim  Probabilistic Tracking in a Metric Space  Toyama and Blake  
Nov. 26  Josh Wills  Stereo from Uncalibrated Cameras  Hartley, Gupta and Chang  
Nov. 28  Thanksgiving holiday  
Dec. 3  Andrew Rabinovich  Robust MultiSensor Image Alignment  Irani and Anandan  
Dec. 5  Project Presentations 
15 minute presentations (abstracts and reports) 
Mallick / Agarwal / Branson / Rabinovich / Wills  ppt, pdf, ppt, ppt, ppt 
Relevant deadlines for students doing projects: CVPR 2003 (Oct. 31/Nov. 4).
CSE 252C fa02 is a graduate seminar devoted to recent research on pattern recognition and computer vision.
Students may enroll for one, two, or four units:
The seminar is open to anyone who has already taken at least one graduate course in computer vision, artificial intelligence, or a closely related area. Appropriate courses at UCSD include CSE 250A, CSE 250B, CSE 252, CSE 254, CSE 253, CogSci 202, ECE 270A, and CSE 275A.
The seminar will meet on Tuesdays and Thursdays from 11:00am12:20pm in Warren Lecture Halls (WLH) 2111. The first meeting will be on Thursday September 26, and the final meeting will be on Thursday December 5, 2002.
Possible topics include:
Students are encouraged to investigate both fundamental algorithmic issues as well as application areas such as biometrics, content based image retrieval, texture synthesis, motion capture, and image based rendering.
The instructor is Serge Belongie, Assistant Professor, AP&M room 4832.
Feel free to send email to sjb+cse252c@cs with any questions.
Computer Vision  A Modern Approach, Forsyth and Ponce
Learning with Kernels, Schölkopf and Smola
Neural Networks for Pattern Recognition, Chris Bishop
Spectral Graph Theory, Fan Chung
Introductory Techniques for 3D Computer Vision Trucco and Verri
Pattern Classification Duda, Hart, and Stork
Pattern Recognition by Theodoridis and Koutroumbas
Kernel Machines Homepage
SVM Tutorial by Osuna, Freund, and Girosi
Lectures Notes on Machine Learning by Rivest and Singh
Each class meeting of 80 minutes will be divided into two parts. First, a student will give a talk lasting about 60 minutes presenting a recent technical paper in detail. In questions during the talk, and in the final 20 minutes, all seminar participants will discuss the paper and the issues raised by it.
Some papers will be theoretical, and some will be applied. Two related applications papers may be discussed together. Theoretical papers will typically be presented and discussed alone, to ensure that mathematical and algorithmic questions are discussed in sufficient depth.
In the first week, we will make a schedule of papers and presentations for the whole quarter. With 10 participants, each student will make two separate presentations. The procedure for one presentation is as follows:
Presentations will be evaluated, in a friendly way but with high standards. Each presentation should be prepared using LaTeX or Powerpoint. You should copy equations, diagrams, charts, and tables as necessary from the paper for the presentation.
For each presentation, we will have a webbased discussion area. Each seminar participant is expected to contribute at least one message to the discussion, before the presentation. A message may ask an interesting question, point out a strength or weakness of the paper, or answer a question asked by someone else. Messages should be thoughtful!
Each student will also do one term project following specific guidelines. The project should be at the frontier of current research, and preferably closely inspired by one of the papers discussed in the class. Project reports will be evaluated using these grading criteria. There is a schedule for handing in a detailed project proposal, a draft project report, and then the final report.
The seminar will have no final exam. Final grades will be based 50% on presentations and participation in class and in the webbased discussions. The other 50% will be the project report.
Most recently updated on July 12, 2002 by Serge Belongie.