 

 
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, CSB 005  
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:  Mohammad (Ehsan) Saberian  
Office hours:  Wednesday, 4:00pm5:00pm at EBU1room 5101  
Teaching Assistant:  TBA  
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 10 Due: April 17  
Problem set 2 [ps, pdf, data] Issued: April 17 Due: April 24  
Problem set 3 [ps, pdf, data] Issued: April 24 Due: May 1  
Problem set 4 [ps, pdf, data] Issued: May 1 Due: May 8  
Problem set 5 [ps, pdf, data] Issued: May 15 Due: May 27  
Problem set 6 [ps, pdf] Issued: May 27 Due: June 5  
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.  

Midterm:  May 8: covers Lectures 210 
Final:  June 9: 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]  