FAVR - Accelerating Direct Volume Rendering for Virtual RealitySystems

Waschk, Andre; Krüger, Jens

doi:10.1109/vis47514.2020.00028

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…The frame rates achieved by the present implementation are consistently higher than those of DVR and of other VDI rendering approaches. Further improvements, such as foveated rendering [4,33], can potentially increase them even further in the future.…”

Section: Discussionmentioning

confidence: 99%

Efficient Raycasting of Volumetric Depth Images for Remote Visualization of Large Volumes at High Frame Rates

Gupta

Günther

Incardona

et al. 2023

2023 IEEE 16th Pacific Visualization Symposium (PacificVis)

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Section: Discussionmentioning

confidence: 99%

Efficient Raycasting of Volumetric Depth Images for Remote Visualization of Large Volumes at High Frame Rates

Gupta

Günther

Incardona

et al. 2023

2023 IEEE 16th Pacific Visualization Symposium (PacificVis)

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“…The method presented in this paper is most closely related to the FAVR approach by Waschk and Krüger [Waschk and Krüger, 2020], i.e., that many of the pixels of the frame-buffer that are sent to the VR systems do not contribute to the perception of the scene. Although the nonuniform resolution distribution of the human-visual-system is well known [Resnikoff, 1989, Valois, 2000, and the use of this phenomenon in computer graphics and visualization is known as foveated imaging [Reder, 1973, Duchowski and Çöltekin, 2007, Murphy et al, 2009, FAVR considers not only human perception but also the nonuniform lens distortion of the HMDs (see Fig.…”

Section: Introductionmentioning

confidence: 99%

Embracing Raycasting for Virtual Reality

Waschk¹,

Krüger²

2022

CSRN

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This paper proposes an acceleration method for direct volume rendering (DVR). Our approach works like a wrapper or braces surrounding raycasting implementations and requires very few changes to the existing code. Visualization systems can significantly improve their rendering performance in virtual reality setups and make DVR feasible in these environments. The first step—the opening brace—modifies the initial ray construction by adaptively reducing the ray density, hence feeding fewer rays to the raycaster. The second brace step is a composting computation after the ray traversal that re-samples the raycasting results across the screen to reconstruct the final image. The rendering resolution is adapted during run-time to the specifications of the VR hardware and the performance of the renderer to guarantee stable and high refresh rates necessary to avoid severe cyber-sickness symptoms. The presented method utilizes gaze-dependent resolution levels tailored towards the human visual system (HVS) and hardware characteristics found in state-of-the-art head-mounted displays (HMDs). The resolution, and therefore the number of processed fragments during ray traversal, is reduced in the peripheral vision, delivering unnoticeable losses in image quality while providing a significant gain in rendering performance

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