358 Works

PBmapclust: Mapping and Clustering the Protein Conformational Space Using a Structural Alphabet

Iyanar Vetrivel, Lionel Hoffmann, Sean Guegan, Bernard Offmann & Adele D. Laurent
Analyzing the data from molecular dynamics simulation of biological macromolecules like proteins is challenging. We propose a simple tool called PBmapclust that is based on a well established structural alphabet called Protein blocks (PB). PBs help in tracing the trajectory of the protein backbone by categorizing it into 16 distinct structural states. PBmapclust provides a time vs. amino acid residue plot that is color coded to match each of the PBs. Color changes correspond to...

Assessing Graphic Designers' Learning Style Profile to Improve Creative Coding Courses

Stig Møller Hansen
This study aimed at assessing graphic design students' preferences for learning to help design school educators teaching Creative Coding programming courses adapt their teaching style to account for the way their students learn. The Felder- Soloman Index of Learning Styles (ILS©) was administered to 77 bachelor-level graphic design students. Compared to students in technical fields, the graphic design students differed by being considerably more intuitive, with an increased preference for active and visual learning. Based...

Learning a Perceptual Quality Metric for Correlation in Scatterplots

Leslie Wöhler, Yuxin Zou, Moritz Mühlhausen, Georgia Albuquerque & Marcus Magnor
Visual quality metrics describe the quality and efficiency of multidimensional data visualizations in order to guide data analysts during exploration tasks. Current metrics are usually based on empirical algorithms which do not accurately represent human perception and therefore often differ from the analysts' expectations. We propose a new perception-based quality metric using deep learning that rates the correlation of data dimensions visualized by scatterplots. First, we created a data set containing over 15,000 pairs of...

The Effects of Adaptive Synchronization on Performance and Experience in Gameplay

Benjamin Watson, Ajinkya Gavane & Rachit Shrivastava
As graphics (GPU) hardware has improved, fixed refresh rate displays became a significant throttle on graphics performance. GPU and display manufacturers therefore introduced adaptive synchronization (Async), which allows displays to adaptively synchronize to GPUs, avoiding rendering stalls and improving frame rate mean and variation. This research is a first experimental examination of the effects of Async on the experience of dedicated (but not professional) gamers. Participants played a first-person shooter (FPS) game, both with Async...

Moving Together: Towards a Formalization of Collective Movement

Juri Buchmüller, Eren Cakmak, Natalia Andrienko, Gennady Andrienko, Jolle W. Jolles & Daniel A. Keim
While conventional applications for spatiotemporal datasets mostly focus on the relation between movers and environment, research questions in the analysis of collective movement typically focus more on relationships and dynamics between the moving entities themselves. Instead of concentrating on origin, destination and the way in between, this inter-mover perspective on spatiotemporal data allows to explain how moving groups are coordinating. Yet, only few visualization and Visual Analytics approaches focus on the relationships between movers. To...

Evaluation of a Mixed Reality based Method for Archaeological Excavation Support

Ronan Gaugne, Quentin Petit, Mai Otsuki & Valérie Gouranton
In the context of archaeology, most of the time, micro-excavation for the study of furniture (metal, ceramics...) or archaeological context (incineration, bulk sampling) is performed without complete knowledge of the internal content, with the risk of damaging nested artefacts during the process. The use of medical imaging coupled with digital 3D technologies, has led to significant breakthroughs by allowing to refine the reading of complex artifacts. However, archaeologists may have difficulties in constructing a mental...

Examining the Components of Trust in Map-Based Visualizations

Cindy Xiong, Lace M. K. Padilla, Kent Grayson & Steven Franconeri
Prior research suggests that perceived transparency is often associated with perceived trust. For some data types, greater transparency in data visualization is also associated with an increase in the amount of information depicted. Based on prior work in economics and political science that has identified four dimensions of transparency, we examined the influence of accuracy, clarity, amount of disclosure, and thoroughness on a decision task where participants relied on map-based visualizations with varying complexity to...

Screen Partitioning Load Balancing for Parallel Rendering on a Multi-GPU Multi-Display Workstation

Yangzi Dong & Chao Peng
Commodity workstations with multiple GPUs have been built by engineers and scientists for real-time rendering applications. As a result, a high display resolution can be achieved by connecting each GPU to a display monitor (resulting in a tiled large display). Using a multi-GPU workstation may not always produce a highly interactive rendering rate due to imbalanced rendering workloads among GPUs. In this work, we propose a parallel load balancing algorithm based on a screen partitioning...

Deep Learning Inverse Multidimensional Projections

Mateus Espadoto, Francisco Caio Maia Rodrigues, Nina S. T. Hirata, Hirata Jr., Roberto & Alexandru C. Telea
We present a new method for computing inverse projections from 2D spaces to arbitrary high-dimensional spaces. Given any projection technique, we train a deep neural network to learn a low-to-high dimensional mapping based on a projected training set, and next use this mapping to infer the mapping on arbitrary points. We compare our method with two recent inverse projection techniques on three datasets, and show that our method has similar or higher accuracy, is one...

Towards Diverse Anime Face Generation: Active Label Completion and Style Feature Network

Hongyu Li & Tianqi Han
It is interesting to use an anime face as personal virtual image to replace the traditional sequence code. To generate diverse anime faces, this paper proposes a style-gender based anime GAN (SGA-GAN), where the gender is directly conditioned to ensure the gender differentiation, and style features serve as a condition to guarantee the style diversity. To extract style features, we train a style feature network (SFN) as a multi-task classifier to simultaneously fulfill gender classification,...

Generation of Walking Sensation by Upper Limb Motion

Gaku Sueta, Naoyuki Saka, Vibol Yem, Tomohiro Amemiya, Michiteru Kitazaki, Makoto Sato & Yasushi Ikei
This paper proposes a method to generate a turning walk sensation to the user by an arm swing display. We assumed a hypothesis that the turning walk sensation is generated by providing different motion profiles of passive arm swing on the left and right arms. We show that turning walk sensation can be generated by presenting arm swing motion with a different flexion ratio of the shoulder joint, depending on the turning radius.

Stochastic Lightcuts

Cem Yuksel
We introduce stochastic lightcuts by combining the lighting approximation of lightcuts with stochastic sampling for efficiently rendering scenes with a large number of light sources. Our stochastic lightcuts method entirely eliminates the sampling correlation of lightcuts and replaces it with noise. To minimize this noise, we present a robust hierarchical sampling strategy, combining the benefits of importance sampling, adaptive sampling, and stratified sampling. Our approach also provides temporally stable results and lifts any restrictions on...

A Mesh Correspondence Approach for Efficient Animation Transfer

Anastasia Moutafidou & Ioannis Fudos
Animating a novel character not only needs a lot of effort and time but also requires the intervention of an experienced user. Moreover, the traditional animation pipeline for a set of characters can be a tedious and cumbersome process which often needs to be repeated several times to correct artifacts. We propose a user-friendly, semi-automated efficient method which is realized in two phases: (i) mesh correspondence, and (ii) skeleton and skinning transfer. We have developed...

Feature Curve Network Extraction via Quadric Surface Fitting

Lu Zhengda, Jianwei Guo, Jun Xiao, Ying Wang, Xiaopeng Zhang & Dong-Ming Yan
Feature curves on 3D shapes provide a high dimensional representation of the geometry and reveal their underlying structure. In this paper, we present an automatic approach for extracting complete feature curve networks from 3D models, as well as generating a high-quality patch layout. Starting from an initial collection of noisy and fragmented feature curves, we first filter non-salient or noisy feature curves by utilizing a quadric surface fitting technique. We then handle the curve intersections...

3D Human Body Skeleton Extraction from Consecutive Surfaces

Yong Zhang, Fei Tan, Shaofan Wang, Dehui Kong & Baocai Yin
Extracting human body skeletons from consecutive surfaces is an important research topic in the fields of computer graphics and human computer interaction, especially in posture estimation and skeleton animation. Current approaches mainly suffer from following problems: insufficient time and space continuity, not robust to background, ambient noise, etc. Our approach is to improve against these shortcomings. This paper proposes a 3D human body skeleton extraction method from consecutive meshes. We extract the consistent skeletons from...

External Forces Guided Fluid Surface and Volume Reconstruction from Monocular Video

Xiaoying Nie, Yong Hu, Zhiyuan Su & Xukun Shen
We propose a novel method to reconstruct fluid's volume movement and surface details from just a monocular video for the first time. Although many monocular video-based reconstruction methods have been developed, the reconstructed results are merely one layer of geometry surface and lack physically correct volume particles' attribute and movement. To reconstruct 3D fluid volume, we define two kinds of particles, the target particles and the fluid particles. The target particles are extracted from the...

Towards Biomechanically and Visually Plausible Volumetric Cutting Simulation of Deformable Bodies

Yinling Qian, Wenbin Huang, Weixin Si, Xiangyun Liao, Qiong Wang & Pheng-Ann Heng
Due to the simplicity and high efficiency, composited finite element method(CFEM) based virtual cutting attracted much attention in the field of virtual surgery in recent years. Even great progress has been made in volumetric cutting of deformable bodies, there are still several open problems restricting its applications in practical surgical simulator. First among them is cutting fracture modelling. Recent methods would produce cutting surface immediately after an intersection between the cutting plane and the object....

LPaintB: Learning to Paint from Self-Supervision

Biao Jia, Jonathan Brandt, Radomír Mech, Byungmoon Kim & Dinesh Manocha
We present a novel reinforcement learning-based natural media painting algorithm. Our goal is to reproduce a reference image using brush strokes and we encode the objective through observations. Our formulation takes into account that the distribution of the reward in the action space is sparse and training a reinforcement learning algorithm from scratch can be difficult. We present an approach that combines self-supervised learning and reinforcement learning to effectively transfer negative samples into positive ones...

A Psychophysical Analysis of Fabricated Anisotropic Appearance

Jiri Filip, Martina Kolafová & Radomir Vávra
Many materials change surface appearance when observed for fixed viewing and lighting directions while rotating around its normal. Such distinct anisotropic behavior manifests itself as changes in textural color and intensity. These effects are due to structural elements introducing azimuthally-dependent behavior. However, each material and finishing technique has its unique anisotropic properties which are often difficult to control. To avoid this problem, we study controlled anisotropic appearance introduced by means of 3D printing. Our work...

Gaze Attention and Flow Visualization using the Smudge Effect

Sangbong Yoo, Seongmin Jeong, Seokyeon Kim & Yun Jang
Many advanced gaze visualization techniques have been developed continuously based on the fundamental gaze visualizations such as scatter plots, attention map, and scanpath. However, it is not easy to locate challenging visualization techniques that resolve the limitations presented in the conventional gaze visualizations. Therefore, in this paper, we propose a novel visualization applying the smudge technique to the attention map. The proposed visualization intuitively shows the gaze flow and AoIs (Area of Interests) of an...

Connectivity-preserving Smooth Surface Filling with Sharp Features

Thibault Lescoat, Pooran Memari, Jean-Marc Thiery, Maks Ovsjanikov & Tamy Boubekeur
We present a method for constructing a surface mesh filling gaps between the boundaries of multiple disconnected input components. Unlike previous works, our method pays special attention to preserving both the connectivity and large-scale geometric features of input parts, while maintaining efficiency and scalability w.r.t. mesh complexity. Starting from an implicit surface reconstruction matching the parts' boundaries, we first introduce a modified dual contouring algorithm which stitches a meshed contour to the input components while...

RegionSketch: Interactive and Rapid Creation of 3D Models with Rich Details

Shuai Liu, Fei Hou, Aimin Hao & Hong Qin
In this paper, we articulate a new approach to interactive generation of 3D models with rich details by way of sketching sparse 2D strokes. Our novel method is a natural extension of Poisson vector graphics (PVG). We design new algorithms that distinguish themselves from other existing sketch-based design systems with three unique features: (1) A novel sketch metaphor to create freeform surface based on Poisson's equation, which is simple, intuitive, and free of ambiguity; (2)...

Preliminary Study on Surface Texture to Manipulate Perceived Softness of 3D Printed Objects

Motoki Miyoshi, Parinya Punpongsanon, Daisuke Iwai & Kosuke Sato
Previous studies have attempted to manipulate the elastic properties of products from elements such as different materials and internal structures. In this paper, we investigate whether we can manipulate the softness perceived by the surface texture when using the FDM-3D printer. We investigated the perceived softness of the surface texture provided by Tymms et al., in which cones of 1 mm in height are arranged, by a subject experiment. From the experimental results, it was...

A Construction Kit for Visual Exploration Interfaces

Mandy Keck & Rainer Groh
With a continuously increasing amount of data and resources on the internet and in large document collections, effective visual exploration interfaces are becoming more and more important. In recent years, many novel approaches have been proposed for the exploration of complex, multidimensional data sets. However, little guidance is available for designers to create similar solutions and to reuse established patterns. In this paper, we propose a construction kit for visual exploration interfaces. It provides a...

Registration Year

  • 2019
    358

Resource Types

  • Text
    358