Perceptual Models of Preference in 3D Printing Direction

Figure 1: Optimization of printing directions has mainly focused on structural stability and material cost. We develop a perceptual model to find optimal printing directions that preserve important visual features. In comparison to alternative methods, our technique avoids placing support structures on important regions to prevent damage in the final printed model. (Left) Support structures resulting from default orientation. (Middle) Result by Autodesk MeshMixer. (Right) Our result. This paper introduces a perceptual model for determining 3D print-ing orientations. Additive manufacturing methods involving low-cost 3D printers often require robust branching support structures to prevent material collapse at overhangs. Although the designed shape can successfully be made by adding supports, residual ma-terial remains at the contact points after the supports have been re-moved, resulting in unsightly surface artifacts. Moreover, fine sur-face details on the fabricated model can easily be damaged while removing supports. To prevent the visual impact of these artifacts, we present a method to find printing directions that avoid placing supports in perceptually significant regions. Our model for prefer-ence in 3D printing direction is formulated as a combination of met-rics including area of support, visual saliency, preferred viewpoint and smoothness preservation. We develop a training-and-learning methodology to obtain a closed-form solution for our perceptual model and perform a large-scale study. We demonstrate the per-formance of this perceptual model on both natural and man-made objects