Difference between revisions of "Directionality Analysis"
From ISLAB/CAISR
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=== Teaching Material === | === Teaching Material === | ||
| − | |||
Get slides from Google docs (ppt) [https://drive.google.com/open?id=0B95UheoCtOzoQjhxWHhKYlR2WEk&authuser=0 here] | Get slides from Google docs (ppt) [https://drive.google.com/open?id=0B95UheoCtOzoQjhxWHhKYlR2WEk&authuser=0 here] | ||
| + | |||
| + | [[Image:edges_corners_lines_circles.png|250px]] | ||
=== References and sources === | === References and sources === | ||
| − | R. Szeliski, “Computer Vision: Algorithms and Applications”, Springer 2010 | + | {| class="wikitable" |
| + | |- | ||
| + | |'''R. Szeliski, “Computer Vision: Algorithms and Applications”, Springer 2010''' | ||
* Sections 4.2.1 (edges), 4.3.2 (Hough) | * Sections 4.2.1 (edges), 4.3.2 (Hough) | ||
* Full book available online: http://szeliski.org/Book/ | * Full book available online: http://szeliski.org/Book/ | ||
| + | |} | ||
| − | + | {| class="wikitable" | |
| − | Simon J.D. Prince, “Computer Vision: Models, Learning, and Inference”, Cambridge University Press, 2012 | + | |- |
| + | |'''Simon J.D. Prince, “Computer Vision: Models, Learning, and Inference”, Cambridge University Press, 2012''' | ||
* Sections 13.1.3 (edges), 13.2 (Canny, Harris) | * Sections 13.1.3 (edges), 13.2 (Canny, Harris) | ||
* Full book available online: http://www.computervisionmodels.com/ | * Full book available online: http://www.computervisionmodels.com/ | ||
| + | |} | ||
| − | + | {| class="wikitable" | |
| − | R. Klette, “Concise Computer Vision”, Springer, 2014 | + | |- |
| + | |'''R. Klette, “Concise Computer Vision”, Springer, 2014''' | ||
* Sections 2.3.3, (edges), 2.3.4 (corners), 2.4. (edges), 3.4 (lines and circles) | * Sections 2.3.3, (edges), 2.3.4 (corners), 2.4. (edges), 3.4 (lines and circles) | ||
* Get [https://drive.google.com/open?id=0B95UheoCtOzobnhLXzhfRnNxUnc&authuser=0 chapter 2] and [https://drive.google.com/open?id=0B95UheoCtOzobnhLXzhfRnNxUnc&authuser=0 chapter 3] | * Get [https://drive.google.com/open?id=0B95UheoCtOzobnhLXzhfRnNxUnc&authuser=0 chapter 2] and [https://drive.google.com/open?id=0B95UheoCtOzobnhLXzhfRnNxUnc&authuser=0 chapter 3] | ||
| + | |} | ||
| Line 39: | Line 47: | ||
Get slides from Google docs (ppt) [https://drive.google.com/open?id=0B95UheoCtOzoSXBGbnZjdkZBSm8&authuser=0 here] | Get slides from Google docs (ppt) [https://drive.google.com/open?id=0B95UheoCtOzoSXBGbnZjdkZBSm8&authuser=0 here] | ||
| + | |||
| + | [[Image:structure_tensor.png|250px]] | ||
| Line 44: | Line 54: | ||
| − | “Hard” references (full mathematical description): | + | “Hard” references (with full mathematical description): |
| − | J. Bigun, Vision with Direction, Springer, 2006 | + | {| class="wikitable" |
| + | |- | ||
| + | |'''J. Bigun, Vision with Direction, Springer, 2006''' | ||
* Chapters 10, 11 | * Chapters 10, 11 | ||
| + | |} | ||
| − | + | {| class="wikitable" | |
| − | J. Bigun, T. Bigun, K.Nilsson, Recognition by Symmetry Derivatives and the Generalized Structure Tensor, IEEE Trans on Pattern Analysis and Machine Intelligence, vol. 26, n. 12, December 2004 | + | |- |
| − | + | |'''J. Bigun, T. Bigun, K.Nilsson, Recognition by Symmetry Derivatives and the Generalized Structure Tensor, IEEE Trans on Pattern Analysis and Machine Intelligence, vol. 26, n. 12, December 2004''' | |
| + | |} | ||
A more “soft” source with a light, introductory description is: | A more “soft” source with a light, introductory description is: | ||
| − | D. Teferi, Recognition and Evaluation by Video Synthesis Methods and Symmetry Features, PhD Thesis, Chalmers University of Technology, 2009 | + | {| class="wikitable" |
| + | |'''D. Teferi, Recognition and Evaluation by Video Synthesis Methods and Symmetry Features, PhD Thesis, Chalmers University of Technology, 2009''' | ||
* Sections 2.4, 5.2) | * Sections 2.4, 5.2) | ||
* Get it [https://drive.google.com/file/d/0B95UheoCtOzoZ3BtLW1tbE40a1U/view?usp=sharing here] | * Get it [https://drive.google.com/file/d/0B95UheoCtOzoZ3BtLW1tbE40a1U/view?usp=sharing here] | ||
| + | |} | ||
Revision as of 19:12, 7 January 2015
| |
| Directionality Analysis | |
|---|---|
| Contact: Fernando Alonso-Fernandez |
Welcome to this lecture on Directionality Analysis.
Contents
[hide]Part 1: Edges, corners, lines, circles
Teaching Material
Get slides from Google docs (ppt) here
References and sources
R. Szeliski, “Computer Vision: Algorithms and Applications”, Springer 2010
|
Simon J.D. Prince, “Computer Vision: Models, Learning, and Inference”, Cambridge University Press, 2012
|
| R. Klette, “Concise Computer Vision”, Springer, 2014 |
Part 2: Structure tensor
Teaching Material
Get slides from Google docs (ppt) here
References and sources
“Hard” references (with full mathematical description):
J. Bigun, Vision with Direction, Springer, 2006
|
| J. Bigun, T. Bigun, K.Nilsson, Recognition by Symmetry Derivatives and the Generalized Structure Tensor, IEEE Trans on Pattern Analysis and Machine Intelligence, vol. 26, n. 12, December 2004 |
A more “soft” source with a light, introductory description is:
D. Teferi, Recognition and Evaluation by Video Synthesis Methods and Symmetry Features, PhD Thesis, Chalmers University of Technology, 2009
|
