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Conformal Geometric Algebra in Stochastic Optimization Problems ...

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212 CHAPTER 8. APPLICATIONS IN OMNIDIRECTIONAL VISION<br />

8.2.2 Initial Estimates<br />

In case of the po<strong>in</strong>t-l<strong>in</strong>e method simply the approved geometric technique <strong>in</strong>troduced<br />

<strong>in</strong> chapter 4, which is also used <strong>in</strong> section 7.3 to provide the <strong>in</strong>itial estimate,<br />

is employed.<br />

The <strong>in</strong>itial estimate for the l<strong>in</strong>e-plane estimation can be provided at very low costs.<br />

Moreover, it shortens the overall computation time. The aim is to rotate the model<br />

such that the unit direction vectors, denoted by { ˆ d 1...N }, of the l<strong>in</strong>es come to lie on<br />

the respective projection planes. Let the normal vectors of the planes be given by<br />

{ˆn 1...N }. Hence pre-align<strong>in</strong>g the model means f<strong>in</strong>d<strong>in</strong>g a rotation matrix R ∈ � 3×3<br />

such that<br />

(∀i): ˆn T i R ˆ di = 0.<br />

By Rodrigues’s formula (3.65), it is known that the matrix R describ<strong>in</strong>g a rotation<br />

through angle θ about a fixed axis, given by a unit normal vector â = [a1;a2; a3],<br />

can be calculated by<br />

R = exp(θA)<br />

For small angles,<br />

= I3 + s<strong>in</strong>θ A + (1 − cos θ)A 2 ,<br />

R ≈ I3 + θA<br />

A :=<br />

⎡ ⎤<br />

0 −a3 a2<br />

⎣ a3 0 −a1⎦.<br />

−a2 a1 0<br />

can be used as a good approximation. With this relationship and due to the skew<br />

symmetric structure of A ′ := θA, it is possible to solve for a ′ = [θa1; θa2; θa3]: each<br />

correspondence pair (ˆni, ˆ di) gives one row<br />

⇐⇒<br />

⇐⇒<br />

ˆn T i A ′ ˆ di = −ˆn T i ˆ di<br />

vec( ˆ diˆn T i ) T vec(A ′ ) = −ˆn T i ˆ di<br />

( ˆ di3ˆni2 − ˆ di2ˆni3)a ′ 1 + ( ˆ di1ˆni3 − ˆ di3ˆni1) a ′ 2 + ( ˆ di2ˆni1 − ˆ di1ˆni2)a ′ 3 = −ˆn T i ˆ di<br />

of an overdeterm<strong>in</strong>ed system of l<strong>in</strong>ear equations. Us<strong>in</strong>g the solution a ′ a first approximation<br />

R [1] of R can be computed. After transform<strong>in</strong>g the l<strong>in</strong>es by means<br />

of R [1] , the method can be reapplied. Any such succeed<strong>in</strong>g iteration yields a new<br />

rotation until the procedure is stopped because the l<strong>in</strong>es were close enough to the<br />

planes. It can be <strong>in</strong>ferred that after t iterations<br />

R ≈ R [t] . ..R [2] R [1] .<br />

The convergence of this method is analyzed <strong>in</strong> [102] with the result that very few<br />

(below five) iterations are necessary to ma<strong>in</strong>ta<strong>in</strong> a high accuracy, even if the amount<br />

of rotation is nearly 180 ◦ (and despite assum<strong>in</strong>g small angles). What makes this<br />

technique so effective is the detour via the Lie algebra so(3) <strong>in</strong>stead of directly<br />

search<strong>in</strong>g the Lie group SO(3), which comprises R, see section 4.6.

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