The Experts below are selected from a list of 6 Experts worldwide ranked by ideXlab platform

Mathieu Desbrun - One of the best experts on this subject based on the ideXlab platform.

  • Tightening the Precision of Perspective Rendering
    Journal of Graphics Tools, 2012
    Co-Authors: Paul Upchurch, Mathieu Desbrun
    Abstract:

    Abstract Precise depth calculation is of crucial importance in graphics rendering. Improving precision raises the quality of all downstream graphical techniques that rely on computed depth (e.g., depth buffers, soft and hard shadow maps, screen-space ambient occlusion, and 3D stereo projection). In addition, the domain of correctly renderable scenes is expanded by allowing larger far-to-near plane ratios and smaller depth separation between mesh elements. Depth precision is an ongoing problem because visible artifacts continue to plague applications from interactive games to scientific visualizations despite advances in graphics hardware. In this article we present and analyze two methods that greatly impact visual quality by automatically improving the precision of depth values calculated in a standard Perspective-Divide rendering system such as OpenGL or DirectX. The methods are easy to implement and compatible with 1/Z depth-value calculations. The analysis can be applied to any depth projection based ...

Paul Upchurch - One of the best experts on this subject based on the ideXlab platform.

  • Tightening the Precision of Perspective Rendering
    Journal of Graphics Tools, 2012
    Co-Authors: Paul Upchurch, Mathieu Desbrun
    Abstract:

    Abstract Precise depth calculation is of crucial importance in graphics rendering. Improving precision raises the quality of all downstream graphical techniques that rely on computed depth (e.g., depth buffers, soft and hard shadow maps, screen-space ambient occlusion, and 3D stereo projection). In addition, the domain of correctly renderable scenes is expanded by allowing larger far-to-near plane ratios and smaller depth separation between mesh elements. Depth precision is an ongoing problem because visible artifacts continue to plague applications from interactive games to scientific visualizations despite advances in graphics hardware. In this article we present and analyze two methods that greatly impact visual quality by automatically improving the precision of depth values calculated in a standard Perspective-Divide rendering system such as OpenGL or DirectX. The methods are easy to implement and compatible with 1/Z depth-value calculations. The analysis can be applied to any depth projection based ...

Edwin Tjoe - One of the best experts on this subject based on the ideXlab platform.

  • Strategies in visuospatial working memory for learning virtual shapes
    Applied Cognitive Psychology, 2009
    Co-Authors: Glenn Gordon Smith, Albert D. Ritzhaupt, Edwin Tjoe
    Abstract:

    This study investigated visuospatial working memory (WM) strategies people use to remember unfamiliar randomly generated shapes in the context of an interactive computer-based visuospatial WM task. In a three-phase experiment with random shapes, participants (n = 94) first interactively determined if two equivalent shapes were rotated or reflected; second, memorized the shape; and third, determined if an imprint in a profile view of the ground was a rotated, reflected imprint of the shape, or an imprint not matching the original shape. Participants self-reported these strategies: Key feature, shape interaction, association/elaboration, holistic/Perspective, Divide and conquer, mental rotation/reflection and others. Participants reporting key features strategy were significantly more accurate on the computer-based visuospatial WM task. These results highlight the importance of strategy in visuospatial WM. Copyright © 2009 John Wiley & Sons, Ltd.

Glenn Gordon Smith - One of the best experts on this subject based on the ideXlab platform.

  • Strategies in visuospatial working memory for learning virtual shapes
    Applied Cognitive Psychology, 2009
    Co-Authors: Glenn Gordon Smith, Albert D. Ritzhaupt, Edwin Tjoe
    Abstract:

    This study investigated visuospatial working memory (WM) strategies people use to remember unfamiliar randomly generated shapes in the context of an interactive computer-based visuospatial WM task. In a three-phase experiment with random shapes, participants (n = 94) first interactively determined if two equivalent shapes were rotated or reflected; second, memorized the shape; and third, determined if an imprint in a profile view of the ground was a rotated, reflected imprint of the shape, or an imprint not matching the original shape. Participants self-reported these strategies: Key feature, shape interaction, association/elaboration, holistic/Perspective, Divide and conquer, mental rotation/reflection and others. Participants reporting key features strategy were significantly more accurate on the computer-based visuospatial WM task. These results highlight the importance of strategy in visuospatial WM. Copyright © 2009 John Wiley & Sons, Ltd.

Albert D. Ritzhaupt - One of the best experts on this subject based on the ideXlab platform.

  • Strategies in visuospatial working memory for learning virtual shapes
    Applied Cognitive Psychology, 2009
    Co-Authors: Glenn Gordon Smith, Albert D. Ritzhaupt, Edwin Tjoe
    Abstract:

    This study investigated visuospatial working memory (WM) strategies people use to remember unfamiliar randomly generated shapes in the context of an interactive computer-based visuospatial WM task. In a three-phase experiment with random shapes, participants (n = 94) first interactively determined if two equivalent shapes were rotated or reflected; second, memorized the shape; and third, determined if an imprint in a profile view of the ground was a rotated, reflected imprint of the shape, or an imprint not matching the original shape. Participants self-reported these strategies: Key feature, shape interaction, association/elaboration, holistic/Perspective, Divide and conquer, mental rotation/reflection and others. Participants reporting key features strategy were significantly more accurate on the computer-based visuospatial WM task. These results highlight the importance of strategy in visuospatial WM. Copyright © 2009 John Wiley & Sons, Ltd.