DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
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.
|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 Time-Varying 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 scale-space: 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 Multi-Sensor 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 11:00am-12:20pm 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 3-D 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 web-based 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 web-based discussions. The other 50% will be the project report.
Most recently updated on July 12, 2002 by Serge Belongie.