Slide 1Feature extraction: Corners 9300 Harris Corners Pkwy, Charlotte, NC Slide 2 Why extract features? Motivation: panorama stitching We have two images – how do we combine…

Slide 1Interest points CSE P 576 Ali Farhadi Many slides from Steve Seitz, Larry Zitnick Slide 2 How can we find corresponding points? Slide 3 Not always easy NASA Mars Rover…

Slide 1 Review Pinhole projection model What are vanishing points and vanishing lines? What is orthographic projection? How can we approximate orthographic projection? Lenses…

Slide 1Recap from Wednesday Two strategies for realistic rendering capture real world data synthesize from bottom up Have existed for 500 years. Both are successful. Attempts…

Slide 1 Lecture 5: Projection CS6670: Computer Vision Noah Snavely Slide 2 Projection Reading: Szeliski 2.1 Slide 3 Projection Reading: Szeliski 2.1 Slide 4 Müller-Lyer…

Slide 1 Lecture 5: Cameras and Projection CS6670: Computer Vision Noah Snavely Slide 2 Reading Szeliski 2.1.3-2.1.6 Slide 3 Announcements Project 1 assigned, see projects…

Slide 1 Lecture 6: Image Warping and Projection CS6670: Computer Vision Noah Snavely Slide 2 Readings Szeliski Chapter 3.5 (image warping), 9.1 (motion models) Slide 3 Announcements…

Slide 1 Slide 2 Slide 3 What is wrong with this picture? Slide 4 Recap from Lecture 2 Pinhole camera model Perspective projections Focal length and field of view Remember…

Slide 1 Lecture 12: Projection CS4670: Computer Vision Noah Snavely “The School of Athens,” Raphael Slide 2 Reading Szeliski 2.1.3-2.1.6 Slide 3 Pinhole camera Add a…

Slide 1 Recap from Friday Pinhole camera model Perspective projections Lenses and their flaws Focus Depth of field Focal length and field of view Slide 2 What is wrong with…