In computer vision, the trifocal tensor (also tritensor) is a 3×3×3 array of numbers (i.e., a tensor) that incorporates all projective geometric relationships among three views. It relates the coordinates of corresponding points or lines in three views, being independent of the scene structure and depending only on the relative motion (i.e., pose) among the three views and their intrinsic calibration parameters. Hence, the trifocal tensor can be considered as the generalization of the fundamental matrix in three views. It is noted that despite the tensor being made up of 27 elements, only 18 of them are actually independent. There is also a so-called calibrated trifocal tensor, which relates the coordinates of points and lines in three views given their intrinsic parameters and encodes the relative pose of the cameras up to global scale, totalling 11 independent elements or degrees of freedom. The reduced degrees of freedom allow for fewer correspondences to fit the model, at the cost of increased nonlinearity.
Correlation slices The tensor can also be seen as a collection of three rank-two 3 x 3 matrices T 1 , T 2 , T 3 {\displaystyle {\mathbf {T} }_{1},\;{\mathbf {T} }_{2},\;{\mathbf {T} }_{3}} known as its correlation slices. Assuming that the projection matrices of three views are P = [ I | 0 ] {\displaystyle {\mathbf {P} }=[{\mathbf {I} }\;|\;{\mathbf {0} }]} , P ′ = [ A | a 4 ] {\displaystyle {\mathbf {P} }'=[{\mathbf {A} }\;|\;{\mathbf {a} }_{4}]} and P ″ = [ B | b 4 ] {\displaystyle {\mathbf {P} ''}=[{\mathbf {B} }\;|\;{\mathbf {b} }_{4}]} , the correlation slices of the corresponding tensor can be expressed in closed form as T i = a i b 4 t − a 4 b i t , i = 1 … 3 {\displaystyle {\mathbf {T} }_{i}={\mathbf {a} }_{i}{\mathbf {b} }_{4}^{t}-{\mathbf {a} }_{4}{\mathbf {b} }_{i}^{t},\;i=1\ldots 3} , where a i , b i {\displaystyle {\mathbf {a} }_{i},\;{\mathbf {b} }_{i}} are respectively the ith columns of the camera matrices. In practice, however, the tensor is estimated from point and line matches across the three views.
Trilinear constraints One of the most important properties of the trifocal tensor is that it gives rise to linear relationships between lines and points in three images. More specifically, for triplets of corresponding points x ↔ x ′ ↔ x ″ {\displaystyle {\mathbf {x} }\;\leftrightarrow \;{\mathbf {x} }'\;\leftrightarrow \;{\mathbf {x} }''} and any corresponding lines l ↔ l ′ ↔ l ″ {\displaystyle {\mathbf {l} }\;\leftrightarrow \;{\mathbf {l} }'\;\leftrightarrow \;{\mathbf {l} }''} through them, the following trilinear constraints hold:
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