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# lec3 - Announcements Read Trucco Verri pp 15-40 Irfanview...

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1 CSE152, Spr 2011 Intro Computer Vision Image Formation and Cameras Introduction to Computer Vision CSE 152 Lecture 3 CSE152, Spr 2011 Intro Computer Vision Announcements • Read Trucco & Verri: pp. 15-40 • Irfanview: http://www.irfanview.com/ is a good Windows utility for manipulating images. Try xv for linux. • Assignment 0: due Thursday 4/7 • I still don’t have a new room for the class. CSE152, Spr 2011 Intro Computer Vision Pinhole Camera: Perspective projection • Abstract camera model - box with a small hole in it Forsyth&Ponce CSE152, Spr 2011 Intro Computer Vision Geometric Aspects of Perspective Projection • Points project to points • Lines project to lines • Angles & distances (or ratios) are NOT preserved under perspective • Vanishing point Image plane CSE152, Spr 2011 Intro Computer Vision The equation of projection Cartesian coordinates: We have, by similar triangles, that (x, y, z) -> (f x/z, f y/z, -f) Ignore the third coordinate, and get ( x , y , z ) ( f x z , f y z ) CSE152, Spr 2011 Intro Computer Vision Euclidean -> Homogenous-> Euclidean In 2-D • Euclidean -> Homogenous: (x, y) -> λ (x,y,1) (can just take λ =1) • Homogenous -> Euclidean: (x, y, z) -> (x/z, y/z) In 3-D • Euclidean -> Homogenous: (x, y, z) -> λ (x,y,z,1) (can just take λ =1) • Homogenous -> Euclidean: (x, y, z, w) -> (x/w, y/w, z/w)

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2 CSE152, Spr 2011 Intro Computer Vision The camera matrix Turn into homogenous coordinates – HC’s for 3D point are (X,Y,Z,1) – HC’s for point in image are (U,V,W) ( x , y , z ) ( f x z , f y z ) CSE152, Spr 2011 Intro Computer Vision Affine Camera Model • Take Perspective projection equation, and perform Taylor Series Expansion about some point (x 0 ,y 0 ,z 0 ). • Drop terms of higher order than linear.
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lec3 - Announcements Read Trucco Verri pp 15-40 Irfanview...

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