System and method for estimating box shape representation of a generally cuboidal object

A method for estimating a three-dimensional (3D) box model of a generally cuboidal object imaged by a 3D vision system that provides a 3D image having 3D points representing imaged surfaces of the cuboidal object, the method comprising the steps of:

• providing a region of interest (ROI) in which the ROI defines a search volume within the 3D image;
• identifying the 3D points that are within the search volume;
• estimating 3D box dimensions that approximate a coarse box shape of the cuboidal object based upon the identified 3D points;
• refining the coarse box shape by determining a projection two-dimensional (2D) height map associated with an imaged surface of the imaged surfaces, and defining at least one of face pixels or non-face pixels associated with the imaged surface;
• identifying bounding positions that define a face of the coarse box shape based upon a distribution of the at least one of face pixels or non-face pixels;
• refining the face of the coarse box shape by determining an associated face thickness;
• and
• deriving an estimated result for the 3D box model including the refined face.

A non-transitory computer readable medium comprising program instructions that, when executed, cause at least one processor to perform:

• receiving, by the at least one processor, a three-dimensional (3D) image of a generally cuboidal object, the 3D image having 3D points representing imaged surfaces of the cuboidal object;
• receiving, by the at least one processor, a region of interest (ROI) in which the ROI defines a search volume within the 3D image;
• identifying the 3D points that are within the search volume;
• estimating 3D box dimensions that approximate a coarse box shape of the cuboidal object based upon the identified 3D points;
• refining the coarse box shape by determining a projection two-dimensional (2D) height map associated with an imaged surface of the imaged surfaces, and defining at least one of face pixels or non-face pixels associated with the imaged surface;
• identifying bounding positions that define a face of the coarse box shape based upon a distribution of the at least one of face pixels or non-face pixels;
• refining the face of the coarse box shape by determining an associated face thickness;
• and
• deriving an estimated result for the 3D box model including the refined face.