FDM 3D printers allow massive creativity in personal products, but their potential has been limited due to inability to manipulating material properties. Previous work had demonstrated that the desired roughness could be presented simply by controlling the spatial density of tiny pins on a printed surface. This article offers a means of providing the desired softness perception of a printed surface and the desired roughness to expand the haptic dimension over which a user can exert control. Specifically, we control the softness by manipulating the infill structures of a printed surface. However, it is known that a skin contact area affects softness perception. The roughness, which is controlled by pins' density, may also affect the perceived softness of a printed surface. Therefore, we investigate how the internal structures and the density of the pins affect softness perception. Through psychophysical experiments, we derive a computational model that estimates the perceived softness from the density of the pins and the infill density of a printed surface. c 2021 Society for Imaging Science and Technology.
In this paper, we propose a method to estimate ink layer layout used as an input for 3D printer. This method makes it possible to reproduce a 3D printed patch that gives a desired translucency, which is represented as Line Spread Function (LSF) in this study. Deep neural networks of encoder decoder model is used for the estimation. In a previous research, it is reported that machine learning method is effective to formulate the complex relationship between the optical property such as LSF and the ink layer layout in 3D printer. However, it may be difficult to collect data large enough to train a neural network sufficiently. Especially, although 3D printer is getting more and more widespread, the printing process is still time consuming. Therefore, in this research, we prepare the training data, which is the correspondence between LSF and ink layer layout in 3D printer, by simulating it on a computer. MCML was used to perform the simulation. MCML is a method to simulate subsurface scattering of light for multi-layered media. Deep neural network was trained with the simulated data, and evaluated using a CG skin object. The result shows that our proposed method can estimate an appropriate ink layer layout which reproduce the appearance close to the target color and translucency.
The paper present a method to estimate appearance difference of two 3D objects, such as 3D prints, using an RGB camera under controlled lighting environment. It consists of three parts. Firstly, calculating image color differences after geometry alignment under different light sources. Secondly, estimating glossiness of the objects with a movable light source. And finally, psychophysical data are used to determine the parameters for estimating appearance differences of 3D prints.
3D printing is becoming increasingly popular around the world today. By utilizing 3D printing technology, customized products can be manufactured much more quickly and efficiently with much less cost. However, 3D printing still suffers from low quality surface reproduction compared with 2D printing. One effective approach to improve it is to develop an advanced halftoning algorithm for 3D printing. In this paper, a novel 3D DBS (Direct Binary Search) halftoning algorithm that can cooperate with current 3D printing technology is proposed which can generate high quality surface reproduction.
Immersive Analytics investigates how novel interaction and display technologies may support analytical reasoning and decision making. The Immersive Analytics initiative of Monash University started early 2014. Over the last few years, a number of projects have been developed or extended in this context to meet the requirements of semi- or full-immersive stereoscopic environments. Different technologies are used for this purpose: CAVE2™ (a 330 degree large-scale visualization environment which can be used for educative and scientific group presentations, analyses and discussions), stereoscopic Powerwalls (miniCAVEs, representing a segment of the CAVE2 and used for development and communication), Fishtanks, and/or HMDs (such as Oculus, VIVE, and mobile HMD approaches). Apart from CAVE2™ all systems are or will be employed on both the Monash University and the University of Konstanz side, especially to investigate collaborative Immersive Analytics. In addition, sensiLab extends most of the previous approaches by involving all senses, 3D visualization is combined with multi-sensory feedback, 3D printing, robotics in a scientific-artistic-creative environment.
Based on 2D digital fast and precision inkjet wide-format printing technology and page wide print head technology, we have developed a novel micro 3D stereo digital printing or 3D object accurate and fast production. By using UV curable inkjet technology or IR curable inkjet technology, we can easily and fast solidify the true colorful 3D objects and bring 2D digital technology up to 3D digital printing level. Two types of 3D printers will be addressed to show micro-3D inkjet technology including their various applications on textile, fashion, ceramics, leather, plastics, glass, packaging, personal decorations, detailed stereo sculpture, dental, spine, biotech application, etc..