COMPUTER VISION

Academic Year 2016/2017 - 1° Year - Curriculum Data Science

Teaching Staff: Sebastiano BATTIATO
Credit Value: 6
Taught classes: 24 hours
Term / Semester: 2°

Learning Objectives

to provide an introduction to the computer vision field by presenting the main theroretical basis and related applicative scenario.

Image formation

Low Level Vision: Filters and Features: Edges, Texture, Laplacian Pyramid,Corner Detection (Harris, …), SIFT

Mid level vision: Segmentation (Thresholding, Seeded Region Growing, Statistical Region Merging, ..)

CV application CBIR Retrieval, Video Stabilization, Face detection and Recognition

E. Trucco, A. Verri, “Introductory Techniques for 3-D Computer Vision”, Prentice Hall, 1998

G. Bradski, A. Kaehler, “Learning OpenCV Computer Vision with the OpenCV Library” O'Reilly Media, 2008;

Mubarak Shah, "Fundamentals of Computer Vision" (pdf), 1997

R. Hartley and A. Zisserman, “Multiple View Geometry in Computer Vision”, 2004;

D. A. Forsyth, J. Ponce, “Computer Vision a Modern Approach”, Prentice Hall PTR, 2002;

Richard Szeliski, Computer Vision: Algorithms and Application, Springer 2010