Mobile Volume Rendering: Past, Present and Future

Noguera, José M.; Jiménez, Junior Vega

doi:10.1109/tvcg.2015.2430343

Cited by 30 publications

(12 citation statements)

References 41 publications

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“…However, their method is for lossy compression and the TF cannot be changed on the mobile devices. Here we also refer the reader to additional techniques surveyed by Noguera et al [47].…”

Section: Visualization Of the Compressed Datamentioning

confidence: 99%

Transfer Function-Guided Saliency-Aware Compression for Transmitting Volumetric Data

Park

Gutenko

Kaufman

2020

IEEE Trans. Multimedia

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We introduce a transfer-function-guided 3D blockbased saliency-aware compression scheme for volumetric data that is both content-and spatially-scalable. Salient 3D volumetric blocks are identified and weighted with the help of a transfer function which is used to render the data. We describe our method in the form of a framework for processing, progressive transmission, and visualization of volumetric data on a target device, such as a mobile device with limited computational resources. In particular, we address the transmission bottleneck incurred when transferring 3D volumetric data. Identified salient regions are progressively transmitted to the target device. The received data is rendered progressively in the respective order with a predefined or user-defined transfer function. Our method is developed with medical applications in mind, where preservation of all information is essential for clinical diagnosis. Because our method is integrated into a resolution scalable coding scheme with an integer wavelet transform of the image, it allows the rendering of each significant region at a different resolution up to fully lossless reconstruction. We perform a thorough qualitative and quantitative evaluation of the saliency detection method and the resulting saliency-aware compression schemes. Our results show reduced error in representation of the volumetric data with our method.

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“…However, their method is for lossy compression and the TF cannot be changed on the mobile devices. Here we also refer the reader to additional techniques surveyed by Noguera et al [47].…”

Section: Visualization Of the Compressed Datamentioning

confidence: 99%

Transfer Function-Guided Saliency-Aware Compression for Transmitting Volumetric Data

Park

Gutenko

Kaufman

2020

IEEE Trans. Multimedia

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“…We briefly discuss here the methods that are most closely related to ours. For a wider coverage, we refer the reader to established surveys on modeling and visualization approaches for time‐varying volumetric data [WF08], compression‐domain DVR [BRGIG∗14], GPU‐based large‐scale DVR [BHP15], and mobile DVR [NJ16].…”

Section: Related Workmentioning

confidence: 99%

“…These include exploring animations while changing camera and rendering settings in order to perceive dynamic effects, quick nonlinear temporal browsing to identify interesting time-steps, as well as analyzing a selected time-step to perceive the finest shape details. Moreover, while simulations are computed on large parallel machines and stored on servers, their results are visually explored on graphics PCs, workstations, or mobile setups [NJ16]. We therefore need to move massive amounts of data efficiently from remote storage to local storage and graphics hardware, and also to handle rendering scalability issues.…”

Section: Introductionmentioning

confidence: 99%

A framework for GPU‐accelerated exploration of massive time‐varying rectilinear scalar volumes

Marton¹,

Agus

Gobbetti³

2019

Computer Graphics Forum

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We introduce a novel flexible approach to spatiotemporal exploration of rectilinear scalar volumes. Our out‐of‐core representation, based on per‐frame levels of hierarchically tiled non‐redundant 3D grids, efficiently supports spatiotemporal random access and streaming to the GPU in compressed formats. A novel low‐bitrate codec able to store into fixed‐size pages a variable‐rate approximation based on sparse coding with learned dictionaries is exploited to meet stringent bandwidth constraint during time‐critical operations, while a near‐lossless representation is employed to support high‐quality static frame rendering. A flexible high‐speed GPU decoder and raycasting framework mixes and matches GPU kernels performing parallel object‐space and image‐space operations for seamless support, on fat and thin clients, of different exploration use cases, including animation and temporal browsing, dynamic exploration of single frames, and high‐quality snapshots generated from near‐lossless data. The quality and performance of our approach are demonstrated on large data sets with thousands of multi‐billion‐voxel frames.

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“…This visualization application is available for PC, Android devices, and iOS devices. Real-time visualization methods on mobile device have been proposed [8]. In this study, we use 3D-textured slicing approach for visualization.…”

Section: Real-time Visualization Stagementioning

confidence: 99%

Volume Rendering Method Applied to 3D Edge Impurity Emission in LHD to Produce Projection Image in Arbitrary Plane

Tamura

Kobayashi

et al. 2019

Plasma and Fusion Research

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Understanding edge impurity transport is one of the important issues for fusion devices to control edge radiation distribution for detachment operation and impurity influx to the confinement region. In LHD, the edge magnetic field structure becomes complex stochastic magnetic field. In order to study relation between impurity transport and the magnetic field geometry, 3D edge impurity emission distributions are obtained by a multichannel spectrometer system and tomography scheme. However, it is difficult to understand the threedimensional (3-D) structure. Therefore, we propose a visualization system that employs a volume rendering method. With the proposed system, which can be used on a PC or mobile device, the user can observe a 3D structure in an arbitrary plane. To realize this function, we propose a volume visualization system comprising preprocessing and real-time rendering stages. Therefore, the visualization framerate can exceed 30 frames per second on PCs and approximately six frames per second on mobile devices, although the user frequently changes the position and direction of the camera.

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Mobile Volume Rendering: Past, Present and Future

Cited by 30 publications

References 41 publications

Transfer Function-Guided Saliency-Aware Compression for Transmitting Volumetric Data

Transfer Function-Guided Saliency-Aware Compression for Transmitting Volumetric Data

A framework for GPU‐accelerated exploration of massive time‐varying rectilinear scalar volumes

Volume Rendering Method Applied to 3D Edge Impurity Emission in LHD to Produce Projection Image in Arbitrary Plane

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