Computer graphics is always growing, in both the techniques it employs and the areas in which it’s applied. We continually see waves of new approaches and applications coming from other fields. At first, these new ideas meet some resistance. People question, “Is this really computer graphics?” However, these original, controversial views often become central to computer graphics. This special issue features four new areas of expansion in computer graphics. These new approaches and applications come from recent research in human–computer interaction (HCI) and computer vision. Each of these new areas is a “big thing” that computer graphics practitioners and researchers need to be aware of. Each area has emerged as the result of advanced technologies that have improved data acquisition—whether through devices that sense touch or imaging systems that produce output in multiple sharply defined wavelength bands. The first big thing is “Visualization beyond the Desktop.” Visualization long ago grew past being simply a tool for individual scientists to examine their data. It’s used in virtually every discipline, including the humanities and social sciences. It has become commonplace in public communication—from the 3D visualizations in weather forecasts to interactive analysis of housing prices in online newspapers. To create and interact with visualizations, researchers have for many years discussed post-WIMP (windows, icons, menus, pointing devices) interfaces. New devices such as smart phones with cameras and GPS and multitouch tables have made such interfaces feasible. In their article, Jonathan Roberts and his colleagues present a view of visualization that’s no longer bound to the desktop and includes interactions with all of a user’s senses. The second big thing is “Automatic Emotion Recognition Based on Body Movement Analysis.” New devices such as inexpensive high-resolution cameras have made it possible to extend user interaction to natural movements. In the past, much HCI research investigated detection of human emotion, often under the name “affective computing.” Emotion recognition, particularly from full-body measurements, has reached the point that it’s suitable for incorporation into computer graphics systems such as computer games and intelligent tutors. In their article, Haris Zacharatos and his colleagues present a short survey of emotion recognition. On the basis of the progress so far, they also outline four major lines of inquiry for additional research. The third big thing is “ElectroEncephaloGraphics: Making Waves in Computer Graphics Research.” Electroencephalography (EEG) is well known as a medical-sensing technology for sensing brain activity through electrical measurements on a person’s scalp. Recent research has made EEG devices much less expensive. Furthermore, signalprocessing research has made it possible to detect subtler signals in the often-noisy EEG data. One possible application of EEG is in HCI. However, in their article, Maryam Mustafa and Marcus Magnor explore an alternative application of EEG in graphics. EEG makes it possible to record an individual’s response to viewing images. Rather than explicitly asking subjects questions such as, “which of these images is better?” in computer graphics psychophysical tests, researchers can measure EEG response. This opens a new approach to improving computer graphics techniques by gathering passive, rather than explicit, responses. Mustafa and Magnor give examples of applying this idea to improving rendering techniques.

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下一件大事【客座编辑介绍】

计算机图形学一直在不断发展，无论是在它采用的技术还是应用的领域。我们不断看到来自其他领域的新方法和应用浪潮。起初，这些新想法遇到了一些阻力。人们质疑，“这真的是计算机图形吗？” 然而，这些原创的、有争议的观点往往成为计算机图形学的核心。本期特刊介绍了计算机图形学的四个新扩展领域。这些新方法和应用来自最近对人机交互 (HCI) 和计算机视觉的研究。这些新领域中的每一个都是计算机图形从业者和研究人员需要注意的“大事”。每个领域都是先进技术的结果，这些技术改进了数据采集——无论是通过感应触摸的设备还是在多个明确定义的波段产生输出的成像系统。第一件大事是“超越桌面的可视化”。很久以前，可视化已经不再仅仅是科学家个人检查数据的工具。它几乎用于每个学科，包括人文科学和社会科学。它在公共传播中变得司空见惯——从天气预报中的 3D 可视化到在线报纸中对房价的交互式分析。为了创建可视化并与之交互，研究人员多年来一直在讨论后 WIMP（窗口、图标、菜单、指点设备）界面。带有摄像头、GPS 和多点触控表的智能手机等新设备使此类接口变得可行。在他们的文章中，Jonathan Roberts 和他的同事展示了一种不再局限于桌面的可视化视图，它包括与用户所有感官的交互。第二件大事是“基于身体运动分析的自动情绪识别”。诸如廉价的高分辨率相机之类的新设备使得将用户交互扩展到自然运动成为可能。过去，许多 HCI 研究调查了人类情感的检测，通常以“情感计算”为名。情绪识别，尤其是全身测量，已经达到了适合纳入计算机图形系统（如计算机游戏和智能导师）的程度。在他们的文章中，Haris Zacharatos 和他的同事们展示了一份关于情绪识别的简短调查。在迄今为止取得的进展的基础上，他们还概述了进一步研究的四个主要研究方向。第三件大事是“ElectroEncephaloGraphics：在计算机图形研究中掀起波澜”。脑电图 (EEG) 是众所周知的医学传感技术，通过对人头皮的电测量来感知大脑活动。最近的研究使 EEG 设备的成本大大降低。此外，信号处理研究使得在经常嘈杂的 EEG 数据中检测更微妙的信号成为可能。EEG 的一种可能应用是在 HCI 中。然而，在他们的文章中，Maryam Mustafa 和 Marcus Magnor 探索了 EEG 在图形中的另一种应用。脑电图可以记录个人对查看图像的反应。而不是明确地向受试者提出诸如“这些图像中哪一个更好？”之类的问题。在计算机图形心理物理测试中，研究人员可以测量脑电图反应。这开辟了一种通过收集被动而非明确的响应来改进计算机图形技术的新方法。Mustafa 和 Magnor 给出了将这个想法应用于改进渲染技术的例子。