System and method for improved scoring of 3D poses and spurious point removal in 3D image data

A system in a vision system for estimating a degree of match of a 3D alignment pose of a runtime 3D point cloud with respect to a trained model 3D point cloud comprising:

• a scoring process, operating in a vision system processor, that scores a match of a candidate pose of the runtime 3D point cloud relative to the trained model 3D point cloud, including a visibility check process that is arranged to
• (a) receive an optical center of a 3D camera,
• (b) receive the trained model 3D point cloud,
• (c) receive the runtime 3D point cloud, and
• (d) construct a plurality of line segments from the optical center to a plurality of 3D points in the trained model 3D point cloud or the runtime 3D point cloud at the runtime candidate pose;
• and
• a determination process that, based upon a location of the 3D points along respective line segments, determines whether to exclude or include the 3D points.

A system for removing spurious points from a 3D image of an object comprising:

• a plurality of 3D cameras arranged to acquire images of an object within a working section thereof from a plurality of respective points of view;
• one or more vision system processors configured to operate:
• a visibility process that,
• (a) receives a measured 3D point cloud from a 3D camera in the plurality of 3D cameras,
• (b) generates presumed poses for the object relative to the measured 3D point cloud, and
• (c) uses information relative to location and orientation of the 3D camera with respect to the object to determine visibility of points of the 3D point cloud;
• and
• a composite point cloud generation process that combines the 3D point cloud from the plurality of 3D cameras into a composite 3D point cloud free of spurious points by omitting points that are not corroborated by appearing in a predetermined number of point clouds in which such points are expected to be visible, based on the visibility process.