Sentence examples for projection of points from inspiring English sources
Considering that the use of space in dance is organized according (or in synchrony) to the projected musical cues it is likely that the projection of points generate clusters in space, or point clouds (Figure 4d), which can be clustered, discriminated and organized in different geometries or representations [24].
It refers to the projection of points from a sphere to a plane.
Firstly, in view of Proposition 2.1, it should be pointed out that for any r ′ ∈ ( 0, r ), the projection of points in U ( r ′ ) = { u ∈ H : d K r ( u ) < r ′ } onto the set K r exists and is unique, that is, for any x ∈ U ( r ′ ), the set P K r ( x ) is nonempty and singleton.
Figure 1 (pmb{x_{k+1}}) is the subgradient extragradient projection of point (pmb{x_{k}-beta_{k}f y_{k})}) onto the hypmb{x_{k}-beta_{k}f y_{k}
W angle is measured between this perpendicular and the M-D line (Figure 4) APDI (NPg-FH plane) ± ( NPg-AB) ± (FH-palatal plane) (Figure 5) Wits appraisal Distance between the projection of point A and point B on the occlusal plane (Figure 6) App-Bpp Distance between the projection of point A and point B on the palatal plane (Figure 6) ANB angle (Figure 1) Figure 1 Angular parameter ANB.
Further, we use (P_{C}(x)) to denote the projection of point (xin R^{n}) onto the convex set C, which satisfies the following property: biglVert P_{C}(x -P_{C}(y) bigrVert ^{2}leq Vert x -P_{rt ^{2}- biglVert P_{C} y)-x+y-P_{C}(y) bigrVert ^{2}lequadforall x,yin R^{n}.
In our experiments, we started with the smallest possible ε-distance between any two 1-D projections of points in the given dataset.
The curvature of the distance field can be obtained through the interpolation function's derivatives, i.e. (16) ∇ X 2 d (X ) = ∑ A ∇ X N A (X ) G A The distance field can be used to efficiently compute the closest point projection of a point x to the boundary.
Based on projections of point cloud slicing that correspond to template sectional curves, the method constructs topological relevant information among discrete points, which makes unorganized points ordering and builds up optimal approximated B-spline curve, resamples every curve according to its curvature distribution and performes triangular mesh division on it.
The matrix W thus encodes the geometric contribution of the projection of the points.
This difference can be justified by the fact that the measurements obtained from the 2D technique determine a projection of the points, which in reality are placed on different planes.
