Multi-view Performance Capture of Surface Details

Table 1 User-defined parameters of the energy function \(\mathbf E \), together with their description, values interval and default value

Parameter	Description	Values int.	Def.
\(w_{reg}\)	Regularization weight	[0, 1]	\(5e^{-7}\)
\(w_{temp}\)	Temporal weight	[0, 1]	\(1e^{-7}\)
\(\sigma _s\)	Standard deviation, \(\forall G_s\)	\((0,\infty )\), [mm]	5
\(T_{qt}\)	Quad-tree depth threshold	\([0,log_2(I^{W,H}) ]\)	9
\(T_{fuse}\)	Color similarity for fusion threshold	\([0,\infty )\)	0.05
\(T_{color}\)	Color similarity threshold	\([0,\infty )\)	0.15
\(T_{dist}\)	Threshold on pixel distance	\([0,\infty )\), [px]	30
\({\varDelta }_d\)	Max geodesic distance	\([0,\infty )\), \([\# edges]\)	2

The quad-tree depth threshold \(T_{qt}\) and color similarity threshold \(T_{fuse}\) are used to subdivide the input 2D images as described in Sect. 4.2 and find the Image Gaussians \(G_i\). \(T_{qt}\) can be at most the logarithm in base 2 of the minimum among the image width \(I^W\) and the image height \(I^H\), expressed as \(log_2(I^{W,H})\). The thresholds on color \(T_{color}\) and pixel distance \(T_{dist}\) between Surface \(G_s\) and Image Gaussians \(G_i\) define for each \(G_s\) the subset of \(G_i\) against which the similarity function is evaluated, excluding less contributing Image Gaussians (see Sect. 5.4)