IEEE Computer Graphics and Applications
About: IEEE Computer Graphics and Applications is an academic journal. The journal publishes majorly in the area(s): Computer graphics & Visualization. It has an ISSN identifier of 0272-1716. Over the lifetime, 2830 publication(s) have been published receiving 135437 citation(s).
Topics: Computer graphics, Visualization, Data visualization, Rendering (computer graphics), Information visualization
Papers published on a yearly basis
TL;DR: This work refers one to the original survey for descriptions of potential applications, summaries of AR system characteristics, and an introduction to the crucial problem of registration, including sources of registration error and error-reduction strategies.
Abstract: In 1997, Azuma published a survey on augmented reality (AR). Our goal is to complement, rather than replace, the original survey by presenting representative examples of the new advances. We refer one to the original survey for descriptions of potential applications (such as medical visualization, maintenance and repair of complex equipment, annotation, and path planning); summaries of AR system characteristics (such as the advantages and disadvantages of optical and video approaches to blending virtual and real, problems in display focus and contrast, and system portability); and an introduction to the crucial problem of registration, including sources of registration error and error-reduction strategies.
TL;DR: This work built on another training-based super- resolution algorithm and developed a faster and simpler algorithm for one-pass super-resolution that requires only a nearest-neighbor search in the training set for a vector derived from each patch of local image data.
Abstract: We call methods for achieving high-resolution enlargements of pixel-based images super-resolution algorithms. Many applications in graphics or image processing could benefit from such resolution independence, including image-based rendering (IBR), texture mapping, enlarging consumer photographs, and converting NTSC video content to high-definition television. We built on another training-based super-resolution algorithm and developed a faster and simpler algorithm for one-pass super-resolution. Our algorithm requires only a nearest-neighbor search in the training set for a vector derived from each patch of local image data. This one-pass super-resolution algorithm is a step toward achieving resolution independence in image-based representations. We don't expect perfect resolution independence-even the polygon representation doesn't have that-but increasing the resolution independence of pixel-based representations is an important task for IBR.
TL;DR: In this article, a volume-rendering technique for the display of surfaces from sampled scalar functions of 3D spatial dimensions is discussed, which is not necessary to fit geometric primitives to the sampled data; images are formed by directly shading each sample and projecting it onto the picture plane.
Abstract: The application of volume-rendering techniques to the display of surfaces from sampled scalar functions of three spatial dimensions is discussed. It is not necessary to fit geometric primitives to the sampled data; images are formed by directly shading each sample and projecting it onto the picture plane. Surface-shading calculations are performed at every voxel with local gradient vectors serving as surface normals. In a separate step, surface classification operators are applied to compute a partial opacity of every voxel. Operators that detect isovalue contour surfaces and region boundary surfaces are examined. The technique is simple and fast, yet displays surfaces exhibiting smooth silhouettes and few other aliasing artifacts. The use of selective blurring and supersampling to further improve image quality is described. Examples from molecular graphics and medical imaging are given. >
TL;DR: This work uses a simple statistical analysis to impose one image's color characteristics on another by choosing an appropriate source image and applying its characteristic to another image.
Abstract: We use a simple statistical analysis to impose one image's color characteristics on another. We can achieve color correction by choosing an appropriate source image and apply its characteristic to another image.
TL;DR: The NavShoe device provides not only robust approximate position, but also an extremely accurate orientation tracker on the foot, which can greatly reduce the database search space for computer vision, making it much simpler and more robust.
Abstract: A navigation system that tracks the location of a person on foot is useful for finding and rescuing firefighters or other emergency first responders, or for location-aware computing, personal navigation assistance, mobile 3D audio, and mixed or augmented reality applications. One of the main obstacles to the real-world deployment of location-sensitive wearable computing, including mixed reality (MR), is that current position-tracking technologies require an instrumented, marked, or premapped environment. At InterSense, we've developed a system called NavShoe, which uses a new approach to position tracking based on inertial sensing. Our wireless inertial sensor is small enough to easily tuck into the shoelaces, and sufficiently low power to run all day on a small battery. Although it can't be used alone for precise registration of close-range objects, in outdoor applications augmenting distant objects, a user would barely notice the NavShoe's meter-level error combined with any error in the head's assumed location relative to the foot. NavShoe can greatly reduce the database search space for computer vision, making it much simpler and more robust. The NavShoe device provides not only robust approximate position, but also an extremely accurate orientation tracker on the foot.
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