lect902h - Szeliski Projective Projective f ( X , t 1) x x...

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•1 Szeliski Projective Projective ) , ( t X f ) 1 , ( - t X f 1 1 2 1 1 4 3 2 1 1 2 1 + + + + = + + + + = y c x c b y a x a y y c x c b y a x a x
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•2 Szeliski (Levenberg-Marquadet) = - = 2 2 )] , ( ) , ( [ e y x f y x f E 1 1 2 1 1 4 3 2 1 1 2 1 + + + + = + + + + = y c x c b y a x a y y c x c b y a x a x Projective min Szeliski (Levenberg-Marquadet) Motion Vector: [ ] T c c b b a a a a 2 1 2 1 4 3 2 1 = m
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•3 Szeliski (Levenberg-Marquadet) l k kl m e m e = a - = k k m e e b b I A m 1 ) ( - + = l Hessian gradient •Homework 1.2 derive expressions for Hessian and gradient vector. 1 1 1 a y y e a x x e a e + = 1 1 2 1 1 4 3 2 1 1 2 1 + + + + = + + + + = y c x c b y a x a y y c x c b y a x a x = - = 2 2 )] , ( ) , ( [ e y x f y x f E
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•4 Hessian =
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This note was uploaded on 06/12/2011 for the course CAP 6411 taught by Professor Shah during the Spring '09 term at University of Central Florida.

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lect902h - Szeliski Projective Projective f ( X , t 1) x x...

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