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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. |
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| Lectures: | TuTh, 12:30p-1:50p, SOLIS 104 |
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| Discussion: |
W 11a - 11:50a, PETER 104 |
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| 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: | Akshaya Purhoit, a k p u r o h i (at) e n g . u c s d . e d u |
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| Office hours: | 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 |
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| Syllabus: | [ps, pdf] | |
| Homework: | Problem set 1 [ps, pdf, data] Issued: April 6 Due: April 13 | |
| Problem set 2 [ps, pdf, data] Issued: April 13 Due: April 20 | ||
| Problem set 3 [ps, pdf,
data] Issued: April 20 Due: April 27 |
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| Problem set 4 [ps, pdf, data] Issued: April 27 Due: May 18 | ||
| Problem set 5 [ps, pdf, data] Issued: May 18 Due: May 30 | ||
| Problem set 6 [ps, pdf] Issued: May 30 Due: June 8 | ||
| 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. |
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| Note: |
Only the computer problem of each assignment will be graded.
You should not turn in the other problems. HW should be submitted to the TA. |
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Midterm: | May 11: covers Lectures 2-10 |
| Final: | June 12: covers all materials | |
| Readings: | Lecture 1: introduction | |
| 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] | |