




This course provides an introduction to image processing and computer vision. We start from the basics of image formation (cameras, light, color), then cover the fundamental concepts in 2D signal processing (2D convolutions, Fourier transforms, etc) and lowlevel vision (edges, texture), and finally move on to higher level problems such as motion analysis, image segmentation, image classification and retrieval. 

Lectures:  TuTh, 12:30p1:50p, Peter 102 

Discussion: 
W 10a  10:50a, SOLIS 110 

F 11a  11:50a, SOLIS 110 

Instructor:  Nuno Vasconcelos, n u n o @ e c e . u c s d . e d u, EBU15602  
Office hours:  Friday, 9:30a10:30a  
Teaching Assistant:  Can Xu 

Office hours:  TBA  
Teaching Assistant:  Zhaowei Cai 

Text:  Computer Vision: a modern approach  
D. Forsyth and J. Ponce, Prentice Hall, 2003  
Secondary text:  Two Dimensional Signal and Image Processing Jae Lim, Prentice Hall, 1990 

Syllabus:  [ps, pdf]  
Homework:  Problem set 1 [ps, pdf, data] Issued: April 9 Due: April 16  
Problem set 2 [ps, pdf, data] Issued: April 16 Due: April 23  
Problem set 3 [ps, pdf,
data] Issued:
April 23 Due: April 30 

Problem set 4 [ps, pdf, data] Issued: April 30 Due: May 7  
Problem set 5 [ps, pdf, data] Issued: May 14 Due: May 26  
Problem set 6 [ps, pdf] Issued: May 26 Due: June 4  
Note:  There are various editions of the book. The numbers of
problems from the book may not be those of your version. In general, you can tell which problem we are talking about, by hints, notes, etc. If you don't, make sure to ask. 

Note: 
Only the computer problem of each assignment will be graded.
You should not turn in the other problems. HW should be submitted to
wel017@ucsd.edu 


Midterm:  May 7: covers Lectures 210 
Final:  June 8: covers all materials  
Readings:  Lecture 1: introduction [slides, videos]  
Lecture 2: cameras (sections 11.2.2, 1.3, F&P) [slides, videos]  
Lecture 3: radiometry (chapter 4, F&P) [slides]  
Lecture 4: radiometry, light sources (sections 5.15.2.2, 5.3.1, F&P) [slides,video]  
Lecture 5: color (sections 6.16.3.3, F&P)[slides]  
Lecture 6: 2D DSP (chapter 1, Lim; chapter 7, F&P)[slides]  
Lecture 7: 2D DSP, Fourier transforms (chapter 1, Lim; chapter 7, F&P)[slides]  
Lecture 8: filtering, smoothing and noise (chapter 8, F&P) [slides]  
Lecture 9: edges (chapter 8, F&P) [slides]  
Lecture 10: edges, interpolation, templates (chapter 8, F&P) [slides]  
Lecture 11: midterm review [problems]  
Lecture 12: midterm  
Lecture 13: 2D DFT (chapter 3, Lim; chapter 7, F&P) [slides, video]  
Lecture 14: 2DDFT (chapter 3, Lim) [slides]  
Lecture 15: DCT (chapter 3, Lim) [slides]  
Lecture 16: scale, pyramids, and texture (chapter 9, F&P) [slides]  
Lecture 17: least squares [slides] (section 15.2, F&P; section 3.3 Strang)  
Lecture 18: motion, least squares [slides] (paper by Lucas and Kanade)  
Lecture 19: MPEG [slides]  
Lecture 20: JPEG [slides]  
Extra material:  Linear Algebra and DSP [slides]  