Models partition for 3D printing objects using skeleton

Purpose It is a challenge to print a model with the size that is larger than the working volume of a three-dimensional (3D) printer. The purpose of this paper is to present a feasible approach to divide a large model into small printing parts to fit the volume of a printer and then assemble these parts into the final model. Design/methodology/approach The proposed approach is based on the skeletonization and the minima rule. The skeleton of a printing model is first extracted using the mesh contraction and the principal component analysis. The 3D model is then partitioned preliminarily into many smaller parts using the space sweep method and the minima rule. The preliminary partition is finally optimized using the greedy algorithm. Findings The skeleton of a 3D model can effectively represent a simplified version of the geometry of the 3D model. Using a model’s skeleton to partition the model is an efficient way. As it is generally desirable to have segmentations at concave creases and seams, the cutting position should be located in the concave region. The proposed approach can partition large models effectively to well retain the integrity of meaningful parts. Originality/value The proposed approach is new in the rapid prototyping field using the model skeletonization and the minima rule. Based on the authors’ knowledge, there is no method that concerns the integrity of meaningful parts for partitioning. The proposed method can achieve satisfactory results by the integrity of meaningful parts and assemblability for most 3D models.

Part Boundaries Alter the Perception of Transparency

The perception of transparency is a remarkable feat of human vision: A single stimulation at the retina is interpreted as arising from two (or more) distinct surfaces, separated in depth, in the same visual direction. This feat is intriguing because physical transparency is neither necessary nor sufficient for phenomenal transparency. Many conditions for phenomenal transparency have been studied, including luminance, chromaticity, stereo depth, apparent motion, and structure from motion. Figural conditions have also been studied, primarily by Gestalt psychologists, resulting in descriptive laws. Here we extend, and make precise, these laws using the genericity principle and the minima rule for part boundaries. We report experiments that support the psychological plausibility of these refinements. The results suggest that the formation of visual objects and their parts is an early process in human vision that can precede the representation of transparency.

Parts of Visual Objects: An Experimental Test of the Minima Rule

Three experiments were conducted to test Hoffman and Richards's (1984) hypothesis that, for purposes of visual recognition, the human visual system divides three-dimensional shapes into parts at negative minima of curvature. In the first two experiments, subjects observed a simulated object (surface of revolution) rotating about a vertical axis, followed by a display of four alternative parts. They were asked to select a part that was from the object. Two of the four parts were divided at negative minima of curvature and two at positive maxima. When both a minima part and a maxima part from the object were presented on each trial (experiment 1), most of the correct responses were minima parts (101 versus 55). When only one part from the object—either a minima part or a maxima part—was shown on each trial (experiment 2), accuracy on trials with correct minima parts and correct maxima parts did not differ significantly. However, some subjects indicated that they reversed figure and ground, thereby changing maxima parts into minima parts. In experiment 3, subjects marked apparent part boundaries. 81% of these marks indicated minima parts, 10% of the marks indicated maxima parts, and 9% of the marks were at other positions. These results provide converging evidence, from two different methods, which supports Hoffman and Richards's minima rule.