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Syllabus
Page numbers in the readings column below refer to the required textbook, E. Trucco and A. Verri, Introductory Techniques for 3-D Computer Vision, Prentice Hall, 1998. Additional material will be handed out in class or posted on the table below as appropriate.
Warning: This page is under construction. Materials are missing in particular for items in red. Active links in the Module column point to lecture notes. |
| Module |
Description |
Required Readings |
Optional Readings |
Software and Data |
| Introduction |
purpose, state of the art |
pp. 1-13 |
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| Image Formation |
projection, sensing, color |
pp. 15-40, Cameras, Litwiller, Bayer |
Kolb, Maeda |
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| Image Processing |
filtering (low-pass and median), derivatives, and edges |
pp. 51-82, Filtering, Weiss |
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Matlab smoothing and gradient code |
| Geometric Calibration |
interior and exterior calibration, rectification |
pp. 123-138, 143-145, 155-161 |
|
Matlab camera calibration package (Bouguet) |
| Math Methods |
linear algebra, vectors, rotations |
Lecture notes on geometric calibration and math methods have been split into two separate sets for greater portability. |
| Stereo |
epipolar geometry, correspondence, triangulation |
pp. 139-143, 150-155, 161-175, Stereo, Stereo 2 |
|
The Middlebury stereo web page |
| Motion + class handouts |
detection and tracking of point features, optical flow |
pp. 82-85, 177-199 |
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Matlab code to experiment with SSD tracking |
| Object Tracking |
Kalman filter, condensation, tracking humans |
pp. 199-203, Condensation |
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Matlab code for the Kalman filter. The Condensation web page. |
| Structure from Motion |
multiframe reconstruction under affine and perspective projection geometry |
pp. 203-212, Factorization |
Multibody factorization |
Video demonstrations of the factorization method |
| Texture |
texture descriptors and classification |
pp. 235-237 |
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| 2D Shape |
splines, snakes, PCA descriptors |
pp. 95-121, 262-270 |
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| Project Descriptions |
5-minute student presentations |
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| 3D Shape |
parts, skeletons, surface models, aspect graphs |
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| Recognition |
character classification, pedestrian and face recognition/detection |
pp. 247-249 |
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- Cameras: Wikipedia entry on cameras.
- Kolb: C. Kolb, D. Mitchell, and P. Hanrahan, 1995. A realistic camera model for computer graphics. In Proceedings of the 22nd Annual Conference on Computer Graphics and interactive Techniques S. G. Mair and R. Cook, Eds. SIGGRAPH '95. ACM Press, New York, NY, 317-324.
- Maeda: P. Y. Maeda, P. B. Catrysse, and B. A. Wandel, 2005. Integrating lens design with digital camera simulation. In Proceedings of SPIE -- Volume 5678, Digital Photography, N. Sampat, J. M. DiCarlo, R. J. Motta, Editors, 48-58.
- Litwiller: D. Litwiller, 2001. CCD vs. CMOS: facts and fiction. In Photonics Spectra.
- Bayer: Wikipedia entry on the Bayer pattern. Also look at the Reference and External Links.
- Filtering: C. Tomasi, 2005. Convolution, smooting, and image derivatives.
- Weiss: B. Weiss, 2006. Fast median and bilateral filtering. In ACM SIGGRAPH 2006 Papers. ACM Press, New York, NY, 519-526.
- Stereo: D. Scharstein and R. Szeliski, 2002. A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms. International Journal of Computer Vision, 47(1-3), 7-42.
- Stereo 2: M. Z. Brown, D. Burschka, and G. D. Hager, 2003. Advances in Computational Stereo. IEEE Transactions on Pattern Analysis and Machine Inltelligence, 25(8), 993-1008.
- Condensation: M. Isard and A. Blake, 1998. CONDENSATION—conditional density propagation for visual tracking, International Journal on Computer Vision, 29(1), 5-28.
- Factorization: C.Tomasi and T. Kanade, 1992. Shape and Motion from Image Streams under Orthography: a
Factorization Method. International Journal on Computer Vision, 9(2), 137-154.
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