161C - Digital Signal Processing II
 

 


             

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 low-level vision (edges, texture), and finally move on to higher level problems such as motion analysis, image segmentation, image classification and retrieval.




Lectures: TuTh, 12:30p-1:50p, 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, EBU1-5602

Office hours: Friday, 9:30a-10:30a




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 2-10

Final: June 8: covers all materials




Readings: Lecture 1: introduction [slides, videos]


Lecture 2: cameras (sections 1-1.2.2, 1.3, F&P) [slides, videos]


Lecture 3: radiometry (chapter 4, F&P) [slides]


Lecture 4: radiometry, light sources (sections 5.1-5.2.2, 5.3.1, F&P) [slides,video]


Lecture 5: color (sections 6.1-6.3.3, 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: mid-term review [problems]


Lecture 12: mid-term


Lecture 13: 2D DFT (chapter 3, Lim; chapter 7, F&P) [slides, video]


Lecture 14: 2D-DFT (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]