Artifact-Based Rendering: Harnessing Natural and Traditional Visual Media for More Expressive and Engaging 3D Visualizations

Abstract

Fig. 1. Using traditional physical artistic media as input to the digital visualization pipeline provides a richer visual vocabulary and opens the door for artists to participate in creating more expressive and engaging 3D scientific visualizations. This example helps scientists understand commercially viable macroalgae growth in the Gulf of Mexico by encoding temperature and salinity from remote sensing together with eddy direction and curvature and three nitrate concentrations from computational simulation.Abstract-We introduce Artifact-Based Rendering (ABR), a framework of tools, algorithms, and processes that makes it possible to produce real, data-driven 3D scientific visualizations with a visual language derived entirely from colors, lines, textures, and forms created using traditional physical media or found in nature. A theory and process for ABR is presented to address three current needs: (i) designing better visualizations by making it possible for non-programmers to rapidly design and critique many alternative data-to-visual mappings; (ii) expanding the visual vocabulary used in scientific visualizations to depict increasingly complex multivariate data; (iii) bringing a more engaging, natural, and human-relatable handcrafted aesthetic to data visualization. New tools and algorithms to support ABR include front-end applets for constructing artifact-based colormaps, optimizing 3D scanned meshes for use in data visualization, and synthesizing textures from artifacts. These are complemented by an interactive rendering engine with custom algorithms and interfaces that demonstrate multiple new visual styles for depicting point, line, surface, and volume data. A within-the-research-team design study provides early evidence of the shift in visualization design processes that ABR is believed to enable when compared to traditional scientific visualization systems. Qualitative user feedback on applications to climate science and brain imaging support the utility of ABR for scientific discovery and public communication.

[Retracted] Optimization of the Rapid Design System for Arts and Crafts Based on Big Data and 3D Technology

“…In the local batch construction stage, for each label l and each training sample x i ∈ I, by computing the set kind of k s nearest neighbours with the same l-label value (0 or 1) as x i ∈ I and the set kind of k d nearest neighbours with different l-label values as x i ∈ I, we can construct local batch p i � x i ∈ K nn . p i forms a hyperedge corresponding to a subhypergraph representing the local geometric structure, and the local Laplacian matrix L i can be constructed by defining (3)(4)(5)(6)(7)(8)(9)(10). Correspondingly, in the low-dimensional feature space S, the local batch of x i ′ ∈ S in the low-dimensional feature space can be computed in the same way p i ′ , where x i ′ is the value of x i ∈ I corresponding to the lowdimensional feature space.…”

“…Facing the massive data of SMT, these methods not only have slow analysis speed, low utilization of SMT data, and poor analysis effect but also lack effective validation means; to address these problems, this paper uses emerging technologies such as big data analysis and 3D visualization simulation to develop a big data analysis platform for SMT industry, which can quickly establish business models of SMT and help quality analysts [5]. Using 3D visualization simulation technology, the platform can build the SPI (Solder Paste Inspection) inspection simulation verification module of the SMT production line to verify the analysis results, thus, saving production resources and improving the analysis efficiency and quality of electronic assembly products [6].…”

Generative Design Inspiration for Glyphs with Diatoms

“…We see Diatoms as being part of a larger effort aimed at expanding the vocabulary of visualization design choices and combinations. Echoing Johnson et al [36], we see this effort as a way to avoid converging on a local maximum, a point where most programmatically-generated visualization exhibits a common aesthetic, one with a limited potential to evoke a range of affective responses from viewers. Randomness and designer agency.…”

Artistic Color Virtual Reality Implementation Based on Similarity Image Restoration

“…e physical model-based similarity image restoration method is to improve the degraded image from the physical point of view, and its purpose is to restore the degraded image to its original appearance with the maximum fidelity of the observed degraded image, combined with a priori knowledge [10]. For specific applications, scholars at home and abroad have researched similar image restoration methods, and after years of development, they can be divided into nonblind restoration methods and blind restoration methods according to whether the point expansion function is known or not [11]. Padcharoen et al blind image recovery methods firstly estimate the point expansion function based on the observed image and then use the nonblind recovery method to realize the similarity image recovery [12].…”