# Lecture-7 - Mann & Picard Lecture-7 Mann & Picard...

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1 Lecture-7 Mann & Picard Mann & Picard Projective Projective Flow (weighted) 0 ! " " t y x f f v f u 1 x " " ! # T C b x x A 0 ! " t T f x f u u ! # x % x ! A x " b C T x " 1 % x Optical Flow const. equation Projective transform Projective Flow (weighted) 2 ) ( t X T f u f flow " ! & 2 ) ) 1 (( t T f A " % " " ! & x T f x Cx b x ! (( Ax " b % ( C T x " 1) x ) T & f x " ( C T x " f t ) 2 minimize Projective Flow (weighted) ( (( ) ( ) ( t x T f % ! & & f x a T a ! [ a 1 , a 2 , b 1 , a 3 , a 4 , b 2 , c 1 , c 2 ] T ] , , , , , , , [ 2 2 y x t y x t y y y x x x t f y xyf yf xyf f x xf f y f x f f y f x f % % % % ! • (b) Homework 3 Derive this equation Due Sept 28 Projective Flow (unweighted)

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2 Pseudo-Perspective 1 x " " ! # T C b x x A 2 5 4 8 7 6 5 2 4 3 2 1 y a xy a y a x a a v y xy a x a y a x a a u x " " " " ! " " " " " ! " Taylor Series Bilinear 1 x " " ! # T C b x x A xy a y a x a a y v xy a y a x a a x u 8 7 6 5 4 3 2 1 " " " ! " " " " ! " Taylor Series & remove Square terms Projective Flow (unweighted) 2 ) ( t X T f u f flow " ! & Minimize Bilinear and Pseudo-Perspective ) % ! )) & & t T f q ) ( *+ , - 1 , , , ), 1 , , , ( y x xy f y x xy f y x T ! ) ) T ! f x ( x , y ,1) f y ( x , y c 1 c 2 , - c 1 ! x 2 f x " xyf x c 2 ! xyf x " y 2 f y bilinear Pseudo perspective ( c) homewwork Derive these eqs Sept 28 Algorithm-1 ! Estimate “q” (using approximate model, e.g.
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## This note was uploaded on 10/04/2011 for the course CAP 6411 taught by Professor Shah during the Spring '09 term at University of Central Florida.

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Lecture-7 - Mann & Picard Lecture-7 Mann & Picard...

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