In-Situ Visual Exploration of Multivariate Volume Data Based on Particle Based Volume Rendering

2016 ◽  
Author(s):  
Takuma Kawamura ◽  
Tomoyuki Noda ◽  
Yasuhiro Idomura
Keyword(s):  
Volume Rendering ◽  
Visual Exploration ◽  
Volume Data

scholarly journals Volume rendering using grid computing for large-scale volume data

2009 ◽  
Author(s):  
Nishihashi Kunihiko ◽  
Higaki Toru ◽  
Okabe Kenji ◽  
Raytchev Bisser ◽  
Tamaki Toru ◽  
...  
Keyword(s):  
Grid Computing ◽  
Volume Rendering ◽  
Large Scale ◽  
Volume Data

Determination of alveolar surface area and tension from in situ pressure-volume data

1970 ◽  
Vol 10 (2) ◽  
pp. 159-171 ◽  
Author(s):  
Martin J. Fisher ◽  
Michael F. Wilson ◽  
Kenneth C. Weber
Keyword(s):  
Surface Area ◽  
Volume Data ◽  
Alveolar Surface Area ◽  
Alveolar Surface

Interactive classification for pre-integrated volume rendering of high-precision volume data

2008 ◽  
Vol 70 (6) ◽  
pp. 125-132 ◽  
Author(s):  
Heewon Kye ◽  
Byeong-Seok Shin ◽  
Yeong Gil Shin
Keyword(s):  
High Precision ◽  
Volume Rendering ◽  
Volume Data

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

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.

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

2004 ◽  
Vol 13 (3) ◽  
pp. 355-370 ◽  
Author(s):  
Koichi Hirota ◽  
Masaki Hirayam ◽  
Atsuko Tanaka ◽  
Toyohisa Kaneko
Keyword(s):  
Real Time ◽  
Volume Rendering ◽  
Computation Time ◽  
Surface Rendering ◽  
Volume Data ◽  
Haptic Interaction ◽  
New Approach ◽  
Computation Algorithm ◽  
Future Work ◽  
Constraint Method

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.

scholarly journals Information-assisted volume rendering and visual evaluation through machine intelligence

2021 ◽  
Author(s):  
Naimul M. Khan
Keyword(s):  
Volume Rendering ◽  
Transfer Functions ◽  
Design Method ◽  
Machine Intelligence ◽  
Training Data ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Complex Data ◽  
Volume Data ◽  
Visual Evaluation

Exploration and visualization of complex data has become an integral part of life. But there is a semantic gap between the users and the visualization scientists. The priority of the users is usability while that of the scientists is techniques. Information-Assisted Visualization (IAV) can help bridge this gap, where additional information extracted from the raw data is presented to the user in an easily interpretable way. This thesis proposes some novel machine intelligence based systems for intuitive IAV. The majority of the thesis focuses on Direct Volume Rendering, where Transfer Functions (TF) are used to color the volume data to expose structures. Existing TF design methods require manipulating complex widgets, which may be difficult for the user. We propose two novel approaches towards TF design. In the data-centric approach, we generate an organized representation of the data through clustering and provide the user with some intuitive control over the output in the cluster domain. We use Spherical Self-Organizing Maps (SS)M) as the core of this approach. Instead of manipulating complex widgets, the user interacts with the simple SSOM color-coded lattice to design the TF. In the image-centric approach, the user interaction with the data is direct and minimal. The user interactions create the training data, and supervised classification is used to generate the TF. First, we propose novel supervised classifiers that combine the local information available through Support Vector Machine-based classifiers and the global information available through Nonparametric Discriminant Analysis-based classifiers. Using these classifiers, we propose a TF design method where the user interacts with the volume slices directly to generate the output. Finally, we explore the use of IAV for home-based physical rehabilitation. We propose an information-assisted visual valuation framework which can compare a user’s performance of a physical exercise with that of an expert using our novel Incremental Dynamic Time Warping method and communicate the results visually through our color-mapped skeleton silhouette. All the proposed techniques are accompanied by detailed experimental results comparing them against the state-of-the-art. The results shows the potential of using machine learning techniques to achieve visualization tasks in a simpler yet more effective way.

A differential volume rendering method with second-order difference for time-varying volume data

2003 ◽  
Vol 14 (3) ◽  
pp. 233-254 ◽  
Author(s):  
Shih-Kuan Liao ◽  
Chin-Feng Lin ◽  
Yeh-Ching Chung ◽  
Jim Z.C Lai
Keyword(s):  
Volume Rendering ◽  
Second Order ◽  
Time Varying ◽  
Volume Data ◽  
Order Difference
Sign in / Sign up

Export Citation Format

Share Document