Computing Visual Correspondence with Occlusions via Graph Cuts
Computing Visual Correspondence with Occlusions via Graph Cuts
Computing Visual Correspondence with Occlusions via Graph Cuts
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will use the following formula for correspondence between binary vectors and<br />
configurations:<br />
∀a ∈A 0<br />
∀a ∈A α<br />
f(a) = 1− x(a)<br />
f(a) = x(a)<br />
∀a /∈ Ã f(a) = 0<br />
Let us denote a configuration defined by a vector x as f x .Thus,wehavethe<br />
energy of binary variables:<br />
where<br />
˜E(x) = ˜ Edata(x)+ ˜ Eocc(x)+ ˜ Esmooth(x)+ ˜ Eunique(x)<br />
˜Edata(x) =Edata(f x ),<br />
˜Eocc(x) =Eocc(f x ),<br />
˜Esmooth(x) =Esmooth(f x ),<br />
˜Eunique(x) =Eunique(f x ).<br />
(Eunique(f) encodes the uniqueness constraint: it is zero if f is unique, and<br />
infinity otherwise). Let’s consider each term separately, and show that each<br />
satisfies condition (6).<br />
1. Data term.<br />
˜Edata(x) = <br />
a∈A(f x )<br />
D(a) = <br />
f x (a) · D(a)<br />
AsingletermE a (x) = f x (a) · D(a) depends only on one variable x(a).<br />
Therefore, condition (6) is not violated.<br />
16<br />
a∈ Ã<br />
(7)