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CPS 296.1
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Places and Dates
Announcements
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Lectures |
Module |
Description |
Readings |
Samples and Software |
1 |
Introduction |
Why vision, state of the art, fundamental challenges, course mechanics |
[1] Preface |
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2, 3, 4 |
1. Image Analysis |
Convolution, smoothing, derivatives, median filtering, edge detection |
[1] Ch 7, [1] Ch 8, [2] |
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5 |
2. Programming |
Tips for programming with images |
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6, 7, 8, 9 |
3. Optical Flow |
Definitions, issues, algorithms, with emphasis on Lucas and Kanade |
[3] |
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10, 11, 12, 13 |
4. Segmentation |
For both images and flow. Split/merge methods, clustering, motion layers |
[1] Ch 14, [1] Ch 16, [5], [6], [7] |
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14, 15, 16, 17 |
5. Tracking |
Appearance and motion models, Kalman filtering, particle filters |
[1] Ch 17, [8], [9] |
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Spring Recess |
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18, 19, 20, 21 |
6. Stereo |
Geometry, similarity metrics. Relaxation, dynamic-programming, belief propagation |
[1] Ch 11, [10], [11] |
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22, 23, 24, 25 |
7. Recognition |
Generative models, discriminative classifiers. Features. Sample algorithms |
[1] Ch 22, [1] Ch 23, [12], [13], [14] |
k nearest neighbors on the plane. See also the OpenCV library |
26, 27 |
Discussion |
Principles learned. What we did not cover. Trends & research opportunities |
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Removed for archival
E-mail address:
tomasi@cs.duke.edu
Office Hours: By appointment
Office Location: D213 LSRC
Office Phone: (919) 660-6539
FAX: (919) 660-6519