Abstract: Techniques include systems, computerized methods, and computer readable media for choosing placement of three-dimensional (3D) probes used for evaluating a 3D alignment pose of a runtime 3D image inside a 3D alignment system for estimating the pose of a trained 3D model image in that 3D runtime image. A plurality of features associated with a first plurality of points of interest from a 3D image are generated, wherein each feature includes data indicative of 3D properties of an associated point from the plurality of points of interest. A second plurality of points of interest are selected from among the first plurality of points of interest, based at least in part on the plurality of features associated with the first plurality of points of interest. Placements of a plurality of 3D probes are determined based at least in part on the second plurality of points of interest.

Abstract: Techniques include systems, computerized methods, and computer readable media for choosing placement of three-dimensional (3D) probes used for evaluating a 3D alignment pose of a runtime 3D image inside a 3D alignment system for estimating the pose of a trained 3D model image in that 3D runtime image. A plurality of features associated with a first plurality of points of interest from a 3D image are generated, wherein each feature includes data indicative of 3D properties of an associated point from the plurality of points of interest. A second plurality of points of interest are selected from among the first plurality of points of interest, based at least in part on the plurality of features associated with the first plurality of points of interest. Placements of a plurality of 3D probes are determined based at least in part on the second plurality of points of interest.