Directionality Analysis

Directionality Analysis
Contact: Fernando Alonso-Fernandez

Welcome to this lecture on Directionality Analysis.

This lecture is divided into two parts:

• Part 1 dedicated to the extraction of eges, corners, lines and circles from images
• Part 2 dedicated to the detection of symmetric patterns via the Generalized Structure Tensor

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 Sections 4.2.1 (edges), 4.3.2 (Hough) Full book available online: http://szeliski.org/Book/

Simon J.D. Prince, “Computer Vision: Models, Learning, and Inference”, Cambridge University Press, 2012 Sections 13.1.3 (edges), 13.2 (Canny, Harris) Full book available online: http://www.computervisionmodels.com/

R. Klette, “Concise Computer Vision”, Springer, 2014 Sections 2.3.3, (edges), 2.3.4 (corners), 2.4. (edges), 3.4 (lines and circles) Get chapter 2 and chapter 3

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 Chapters 10, 11

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 Sections 2.4, 5.2) Get it here