Toward a Conceptual Emulation Framework for the Preservation of Archaeological 3D Visualizations

Through the Preservation of Complex Objects Symposia (POCOS), leading researchers and practitioners have managed to propose strategies for preserving digital art and computer games. The same is not true for the preservation of archaeological visualizations. This article therefore discusses the following question: “Can emulation be employed to effectively preserve obsolete computer visualizations from the Archaeology domain?” Guidelines and test results coming from this work would be of great benefit to the archaeological community, and would contribute knowledge to other research communities, specifically those interested in similar data types/3D visualizations.     

The influence of text modality on learning with static and dynamic visualizations

In this study we investigated the influence of text modality on learning with static and dynamic visualizations in a dynamic domain, namely the physical principles underlying fish locomotion. A 2 × 2-design with type of visualization (static vs. dynamic) and text modality (spoken vs. written) as independent variables was used. Concerning learning outcomes, it was hypothesized that (1) learners presented with dynamic visualizations would outperform learners presented with static visualizations, (2) learners presented with spoken text would outperform learners presented with written text, and (3) an interaction between type of visualization and modality would occur: the superiority of dynamic over static visualizations was expected to be more pronounced for spoken compared to written text. Subjective cognitive load measures were assessed and expected to mirror the aforementioned pattern of learning outcomes in accordance with Cognitive Load Theory (i.e., higher extraneous cognitive load (ECL) related to lower learning outcomes). For transfer tasks, the first two hypotheses could be confirmed. However, there was no interaction. Moreover, ECL was rated higher by subjects when learning with static compared to dynamic visualizations, but there were no differences for ECL with respect to the text modality. The results are discussed within the framework of Cognitive Load Theory.     

Learning with dynamic and static visualizations: Realistic details only benefit learners with high visuospatial abilities

Learning environments can nowadays easily be enriched with different presentation formats of visualizations, because computer graphics technology is constantly and rapidly developing. This study investigates the effectiveness of dynamic compared to static visualizations. Moreover, the influence of realistic details in the visualizations as well as learners’ prerequisites in terms of their visuospatial abilities were addressed. Eighty university students were randomly assigned to four conditions of a two-by-two between subjects design with the two independent variables dynamism and realism. Learning outcomes were measured by means of a verbal factual knowledge test about the terminology and visuospatial details and a pictorial recognition test about the dynamic processes. Data analyses revealed no effects for factual knowledge. With respect to recognition, learners with dynamic visualizations outperformed learners with static visualizations. Furthermore, there was an interaction between learners’ visuospatial abilities and the degree of realism in the visualization: learners with lower visuospatial abilities showed better recognition with schematized visualizations, whereas learners with higher visuospatial abilities showed better recognition with realistic visualizations. The results imply that when designing instructional materials, both the type of knowledge that has to be acquired as well as learners’ prerequisites such as their visuospatial abilities need to be considered.     

An algorithm for generating color scales for both categorical and ordinal coding

Previous research has shown multihue scales to be well‐suited to code categorical features and shown lightness scales to be well‐suited to code ordinal quantities. We introduce an algorithm, Motley, that produces color scales varying in both hue and lightness, intended to be effective for both categorical and ordinal coding, allowing users to determine both absolute and relative quantities efficiently and accurately. The algorithm first determines the lightnesses of scale colors to maximize perceived lightness differences and establish the lightness ordering, generating separate search spaces for each scale position. It then selects hues by heuristic search to maximize the discriminability of the scale. It produces scales that are ordered with respect to lightness but unordered with respect to hue and thus more discriminable than typical multihue lightness scales. In an experimental evaluation on human subjects, Motley's scales enabled accurate judgments of relative quantity, with response times superior to unordered multihue scales and comparable to ordered lightness scales, and enabled accuracy and speed of judgments of absolute quantity superior to lightness scales and comparable to multihue scales. Published 2009 Wiley Periodicals, Inc., Col Res Appl, 2010.     

一种多维数据的聚类算法及其可视化研究

提出了一种基于主次属性划分的聚类方法和一种新的数据可视化方法.首先,利用数据的主属性和次属性的特征值对数据集进行聚类;然后,采用彩色刺激光谱投影到RGB颜色空间的原理,通过色度学中麦克斯韦的三角平面坐标色度图对各聚类结果进行可视化显示.实验证明了文中方法算法简单、容易实现,可视化结果有利于用户全面地理解数据,为数据的预测、决策起到重要作用.     

3维立体动画制作的视觉效果评价

目的 视觉效果评价是3维立体动画制作过程中不可忽略的一环。评价过程主要依靠专业人员的行业经验,受人员知识水平、测试环境等因素的影响。针对该问题,提出了一个主客观结合的评价模型。方法 首先建立了一个面向前期制作的三维动画场景数据集用以训练和测试,针对视觉效果评价的两个重要指标:立体感和视觉舒适度,进行主观实验得到相应的分数;提取全局视觉舒适度特征和感兴趣区域立体感特征,使用支持向量回归(SVR)方法,经过训练和测试得到舒适度评价模型和立体感评价模型。结果 通过将性能验证实验得到验证场景的主观分数与评价模型给出的结果进行比对,结果表明,运用评价模型得到的预测分数与观众主观分数基本一致,该模型可以对影响视觉效果的视觉舒适度和立体感予以5级量化评分。结论 本文所提出的视觉舒适度和立体感评价方法,能建立影响视觉效果的特征与主观评分间的关系,用得到的模型预测分数给制作人员一个及时直观的调节依据标准。     

Optimal CNN-based semantic segmentation model of cutting slope images

This paper utilizes three popular semantic segmentation networks, specifically DeepLab v3+, fully convolutional network (FCN), and U-Net to qualitively analyze and identify the key components of cutting slope images in complex scenes and achieve rapid image-based slope detection. The elements of cutting slope images are divided into 7 categories. In order to determine the best algorithm for pixel level classification of cutting slope images, the networks are compared from three aspects: a) different neural networks, b) different feature extractors, and c) 2 different optimization algorithms. It is found that DeepLab v3+ with Resnet18 and Sgdm performs best, FCN 32s with Sgdm takes the second, and U-Net with Adam ranks third. This paper also analyzes the segmentation strategies of the three networks in terms of feature map visualization. Results show that the contour generated by DeepLab v3+ (combined with Resnet18 and Sgdm) is closest to the ground truth, while the resulting contour of U-Net (combined with Adam) is closest to the input images.     

An octree-based multiresolution hybrid framework

The Hybrid Octree (HO) is a new approach to deal with hybrid scenes, (i.e. scenes composed of surface and volume data). The HO codes into a single model a compressed approximation of an isosurface extracted from a volume dataset and a compressed representation of the scalar data. The HO definition and its construction algorithm are provided in the paper. We also describe the capabilities of the HO to efficiently manipulate surface and volume data independently and its facilities to composite and visualize surface and volume data using texture hardware. Special emphasis is given to the HO facilities to support multiresolution. Some examples are presented and the goodness of the model is discussed.     

Spray applications: Part V. Influence of high solid compositions on coatings sprayability

The air-spray patterns of high solid coatings were examined using a Particle Image Velocimeter (PIV) to determine the affects of varying the composition (oligomeric acrylic, oligomeric ester, and melamine resin) and molecular weight of high solid resins in coating formulations on their sprayability. High molecular weight tails (e.g., in the acrylic) are known to increase the elasticity of the fluid, and their presence imparted poor spray behavior (i.e., less misting, presence of ligaments, narrower exit fanning, and higher velocities farther from the nozzle) to the high solid coating. The Sauter Mean Diameter (SMD) of the droplets increased with increasing viscosity, which is dependent on weight average molecular weight of the total components of the blends. High solids stored at 60°C resulted in poorer spray with both increasing storage time and increasing levels of catalyst stored for 2 h. The high solid coatings were Newtonian fluids with no elastic functions associated with shear deformations. The elastic behavior associated with the high molecular weight tails in the acrylic oligomers is related, through their similar variation in spray behavior with HEUR thickened latex coatings in Part IV of this series, to dynamic uniaxial extensional viscosities.

Going to town: Visualized perspectives and navigation through virtual environments

Two experiments examined how spatial learning perspectives support navigation through virtual urban environments. Participants briefly learned the overall layout of a virtual desktop environment, and then were taken on a simulated journey ending at a starting location within the environment. In Experiment 1, during the journey participants watched simulated video feeds either from the front of the vehicle (route perspective), above the vehicle (survey perspective), both feeds simultaneously, or no video at all. Participants then navigated between ten successive landmarks, and we measured indices of spatial and temporal efficiency, and heading error. Results indicated that the route perspective supported a restricted range of local navigation whereas the survey perspective better supported far-space navigation. Experiment 2 demonstrated that the survey perspective also better supports navigation around unexpected detours. Results are discussed with regard to theories of spatial memory and the design of computer-supported spatial visualization technologies.