Difference between revisions of "Directionality Analysis"
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|header2 = '''Contact:''' [[Fernando Alonso-Fernandez]] | |header2 = '''Contact:''' [[Fernando Alonso-Fernandez]] | ||
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Welcome to this lecture on Directionality Analysis. | Welcome to this lecture on Directionality Analysis. | ||
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== Part 1: Edges, corners, lines, circles == | == Part 1: Edges, corners, lines, circles == | ||
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=== Teaching Material === | === Teaching Material === | ||
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== Part 2: Structure tensor == | == Part 2: Structure tensor == | ||
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=== Teaching Material === | === Teaching Material === | ||
Revision as of 18:28, 7 January 2015
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| Directionality Analysis | |
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| Contact: Fernando Alonso-Fernandez |
Welcome to this lecture on Directionality Analysis.
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
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Simon J.D. Prince, “Computer Vision: Models, Learning, and Inference”, Cambridge University Press, 2012
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| 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
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| 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
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