Spatial Constraint Method: A New Approach to Real-Time Haptic Interaction in Virtual Environments

In this paper, we propose an approach to real-time haptic interaction based on the concept of simulating the constraining propertes of space. Research on haptic interaction has been conducted from the points of view of both surface and volume rendering. Most approaches to surface rendering—such as the constraint-based god-object method, the point-based approach, and the virtual proxy approach—have dealt only with the interaction with an object surface. Whereas, in volume rendering approaches, algorithms for representing volume data through interactions in space have been investigated. Our approach provides a framework for the representation of haptic interaction with both surface and space. We discretize the space using a tetrahedral cell mesh and associate a constraining property with each cell. The interaction of the haptic interface points with a volume is simulated using the constraining properties of the cells occupied by this volume. We implemented a fast computation algorithm that works at a haptic rate. The algorithm is robust in that any sudden or quick motion of the user does not disturb the computation, and the computation time for each cycle is independent of the complexity of the model as a whole. To demonstrate the performance of the proposed method, we present experimental results on the interaction with models of varying complexity. Also, we discuss some problems that need to be solved in future work.

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Modeling and volume rendering approach of underwater three-dimensional acoustic energy field

International Journal of Modeling Simulation and Scientific Computing ◽

10.1142/s1793962316500197 ◽

2016 ◽

Vol 07 (03) ◽

pp. 1650019

Author(s):

Yanyang Zeng ◽

Panpan Jia

Keyword(s):

Real Time ◽

Volume Rendering ◽

Underwater Acoustics ◽

Three Dimensional ◽

Texture Mapping ◽

Propagation Model ◽

Acoustic Energy ◽

Frame Rate ◽

Volume Data ◽

Energy Field

The underwater acoustics is primary and most effective method for underwater object detection and the complex underwater acoustics battlefield environment can be visually described by the three-dimensional (3D) energy field. Through solving the 3D propagation models, the traditional underwater acoustics volume data can be obtained, but it is large amount of calculation. In this paper, a novel modeling approach, which transforms two-dimensional (2D) wave equation into 2D space and optimizes energy loss propagation model, is proposed. In this way, the information for the obtained volume data will not be lost too much. At the same time, it can meet the requirements of data processing for the real-time visualization. In the process of volume rendering, 3D texture mapping methods is used. The experimental results are evaluated on data size and frame rate, showing that our approach outperforms other approaches and the approach can achieve better results in real time and visual effects.

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Effects of Different Parameter Settings for 3D Data Smoothing and Mesh Simplification on Towards Near Real-Time 3D Reconstruction of High Resolution Bioceramic Bone Void Filling Medical Images

10.20944/preprints202110.0362.v1 ◽

2021 ◽

Author(s):

Daniel Jie Yuan Chin ◽

Ahmad Sufril Azlan Mohamed ◽

Khairul Anuar Shariff ◽

Mohd Nadhir Ab Wahab ◽

Kunio Ishikawa

Keyword(s):

Real Time ◽

Volume Rendering ◽

Medical Images ◽

Three Dimensional ◽

Mesh Simplification ◽

Surface Rendering ◽

Reconstruction Accuracy ◽

Total Execution Time ◽

Data Smoothing ◽

Dimensional Reconstruction

Three-dimensional reconstruction plays an important role in assisting doctors and surgeons in diagnosing bone defects’ healing progress. Common three-dimensional reconstruction methods include surface and volume rendering. As the focus is on the shape of the bone, volume rendering is omitted. Many improvements have been made on surface rendering methods like Marching Cubes and Marching Tetrahedra, but not many on working towards real-time or near real-time surface rendering for large medical images, and studying the effects of different parameter settings for the improvements. Hence, in this study, an attempt towards near real-time surface rendering for large medical images is made. Different parameter values are experimented on to study their effect on reconstruction accuracy, reconstruction and rendering time, and the number of vertices and faces. The proposed improvement involving three-dimensional data smoothing with convolution kernel Gaussian size 0.5 and mesh simplification reduction factor of 0.1, is the best parameter value combination for achieving a good balance between high reconstruction accuracy, low total execution time, and a low number of vertices and faces. It has successfully increased the reconstruction accuracy by 0.0235%, decreased the total execution time by 69.81%, and decreased the number of vertices and faces by 86.57% and 86.61% respectively.

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New Parallel Technics for GPU, Fast SURF Algorithm

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.g5855.069820 ◽

2020 ◽

Vol 9 (8) ◽

pp. 389-393

Keyword(s):

Real Time ◽

Graphics Processing Unit ◽

Computation Time ◽

Processing Unit ◽

Real Time Processing ◽

Time Usage ◽

Computation Algorithm ◽

Original Application ◽

Graphics Processing ◽

Point Detection

Computer vision algorithms, especially real-time tasks, require intensive computation and reduced time. That’s why many algorithms are developed for interest point detection and description. For instance, SURF (Speeded Up Robust Feature) is extensively adopted in tracking or detecting forms and objects. SURF algorithm remains complex and massive in term of computation. So, it’s a challenge for real time usage on CPU. In this paper we propose a fast SURF parallel computation algorithm designed for Graphics-Processing-Unit (GPU). We describe different states of the algorithm in detail, using several optimizations. Our method can improve significantly the original application by reducing the computation time. Thus, it presents a good performance for real-time processing

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In-Situ Thermal ROM-Based Optimization Using Borg MOEA: A Preliminary Study

ASME 2019 Heat Transfer Summer Conference ◽

10.1115/ht2019-3483 ◽

2019 ◽

Author(s):

Kevin Irick ◽

Erich Brown

Keyword(s):

Real Time ◽

Mechanical Systems ◽

Computation Time ◽

Volume Data ◽

Process Data ◽

Data Volume ◽

Major Bottleneck ◽

Engineering Effort ◽

Heat Transfer System

Abstract High-fidelity computational thermal models (HFMs) of mechanical systems typically incorporate multi-disciplinary data sources to define boundary conditions, constraints, and dynamic system inputs. Oftentimes, HFMs are used during the planning, design, fabrication, testing, and operational phases of the mechanical systems, however, most of that data is processed during the modeling and test phases to discover and verify system responses. This approach can lead to much unused data and engineering effort that could otherwise provide useful information during the operational phases of the systems. One major bottleneck in using HFMs during the operational phase is data volume and computation time. Reduced-order models (ROMs), such as Gaussian processes, can consolidate data volume, data complexity, and time complexity needed for processing HFMs. The Borg multi-objective evolutionary algorithm (MOEA) presents a possible effective approach for processing ROM information in conjunction with real-time true process data to better understand the real-time state of a system. An investigation is being performed into the use of ROMs with the Borg MOEA to capitalize on engineering effort and simulation data that would otherwise be abandoned. This paper discusses the results of such a study in a steady-state conductive-radiative heat transfer system.

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Effects of Different Parameter Settings for 3D Data Smoothing and Mesh Simplification on Near Real-Time 3D Reconstruction of High Resolution Bioceramic Bone Void Filling Medical Images

Sensors ◽

10.3390/s21237955 ◽

2021 ◽

Vol 21 (23) ◽

pp. 7955

Author(s):

Daniel Jie Yuan Chin ◽

Ahmad Sufril Azlan Mohamed ◽

Khairul Anuar Shariff ◽

Mohd Nadhir Ab Wahab ◽

Kunio Ishikawa

Keyword(s):

Real Time ◽

Volume Rendering ◽

Medical Images ◽

Three Dimensional ◽

Mesh Simplification ◽

Surface Rendering ◽

Reconstruction Accuracy ◽

Total Execution Time ◽

Data Smoothing ◽

Dimensional Reconstruction

Three-dimensional reconstruction plays a vital role in assisting doctors and surgeons in diagnosing the healing progress of bone defects. Common three-dimensional reconstruction methods include surface and volume rendering. As the focus is on the shape of the bone, this study omits the volume rendering methods. Many improvements have been made to surface rendering methods like Marching Cubes and Marching Tetrahedra, but not many on working towards real-time or near real-time surface rendering for large medical images and studying the effects of different parameter settings for the improvements. Hence, this study attempts near real-time surface rendering for large medical images. Different parameter values are experimented on to study their effect on reconstruction accuracy, reconstruction and rendering time, and the number of vertices and faces. The proposed improvement involving three-dimensional data smoothing with convolution kernel Gaussian size 5 and mesh simplification reduction factor of 0.1 is the best parameter value combination for achieving a good balance between high reconstruction accuracy, low total execution time, and a low number of vertices and faces. It has successfully increased reconstruction accuracy by 0.0235%, decreased the total execution time by 69.81%, and decreased the number of vertices and faces by 86.57% and 86.61%, respectively.

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Volume Rendering Method for Spatial Seismic Data Based on GPU

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.347-350.2636 ◽

2013 ◽

Vol 347-350 ◽

pp. 2636-2641

Author(s):

Zhong Xiang Duan ◽

Guo He Li

Keyword(s):

Volume Rendering ◽

Spatial Data ◽

Seismic Data ◽

Ray Casting ◽

Surface Rendering ◽

Volume Data ◽

Data Field ◽

Data Volume ◽

Pseudo Color ◽

Ray Casting Algorithm

Volume rendering is one of the focuses in the research and application of computing visualization. On basis of the spatial data volume formally defined,principles and methods are introduced on the division of volume data, computation of resampling and composition of image in the ray casting algorithm. By resampling and compositing with shader, the algorithm is successfully improved in performance by GPU. The application of the algorithm in seismic interpretation is implemented for visualization of spatial seismic data in gray and pseudo-color and a transfer function is designed to highlight the characteristics of stratums in seismic data field, overcoming limitations in the visualization of profiles, slices and surface rendering of seismic data.

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