We present a novel method to visualize high-dimensional dataset as a landscape. The goal is to provide clear and compact representation to reveal the structure of high-dimensional datasets in a way that the size and d...
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We present a novel method to visualize high-dimensional dataset as a landscape. The goal is to provide clear and compact representation to reveal the structure of high-dimensional datasets in a way that the size and distinctiveness of clusters can be easily discerned, and the relationships among single points can be preserved. Our method is network-based, and consists of two main steps: clustering and embedding. First of all, the similarity graph of high-dimensional dataset is constructed based on the Euclidean distances between data points. For clustering, we propose a new network community detection algorithm to calculate the membership-degree of each vertex belonging to each community. For embedding, we bring forward a practical algorithm to obtain an evenly distributed and regularly shaped layout of data points, in a way that the original relationships among single points are preserved. Finally, the landscape-like visualization is produced by assigning altitudes to data points according to their membership-degrees and by inserting control points. In our high-dimensional data visualization, clusters form highlands, and border data points among clusters show up as valleys. The area and altitude of highland indicate the size and distinctiveness of data cluster respectively.
This work focuses on the development of the BrainTool, an embedded application that provides full automated volume segmentation and visualization of a reconstructed 3D mesh of human brains. A brain scan is performed t...
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This work focuses on the development of the BrainTool, an embedded application that provides full automated volume segmentation and visualization of a reconstructed 3D mesh of human brains. A brain scan is performed to acquire a set of voxels using a 3D Magnetic Resonance sampler. The application is executed on embedded (mobile) systems. The tool operates through three principal modules: an automatic segmentation to remove the non-brain structures, a parallel implementation state of art Marching Cubes mesh synthesizer followed by an OpenGL ES rendering step to achieve model interactive visualization. The development of the application is done using two different low cost boards integrating low power state of art CPU and GPU into embedded system on chip; in order to test the solution, samples acquired from MRI equipment commonly available at hospitals are used. The experiments allow to conclude that the Marching Cube algorithm parallelize fairly enough and can be distributed on the available resources reaching scalable performances when executed on laptop and embedded systems. Rendering of complex graphics assets up to 2.7M triangles per model is performed.
At Sólheimajökull glacier in southern Iceland, field evidence has been collected of a Tenth Century jökulhlaup (or glacial outburst flood). It was an exceptional event in terms of generation, scale, mag...
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We present a novel method to modulate influence of diffuse scattering in fluid cavity and reflection at boundary of pulse-echo ultrasound image. A simplified formation of ultrasound model is used to delineate it, and ...
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The fact is that in many Visual Analysis tasks are often used various mapping methods and techniques, inherited from the pre-computer era. Even for Data Exploration, despite of advanced interactive features of modern ...
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The fact is that in many Visual Analysis tasks are often used various mapping methods and techniques, inherited from the pre-computer era. Even for Data Exploration, despite of advanced interactive features of modern hardware and software. These ways of graphical representation with a static design are often rigidly adhered to a specific data structure. With such advantages of compact illustration for print (where paper space is crucial), the statically charts are principally at disadvantage in compositional flexibility. Unlike a paper version, array of interactive capabilities plays an important role in chart implementation for screen displaying. The paper reviews an original approach to categorical data visualization, which takes into account features of the visual perception of form and color, as well as distribution and focusing characteristics of the visual attention, along with advantages of using the interactive computergraphics capabilities.
The proceedings contain 55 papers. The topics discussed include: texture compression in memory and performance-constrained embedded systems;brain medical image fusion based on IHS and log-Gabor with suitable decomposi...
ISBN:
(纸本)9789728939489
The proceedings contain 55 papers. The topics discussed include: texture compression in memory and performance-constrained embedded systems;brain medical image fusion based on IHS and log-Gabor with suitable decomposition scale and orientation for different regions;3D reconstruction of small solar system bodies using photoclinometry by deformation;surface feature sharpening: observation minus calculation (O-C) approach;a study about influenceable parameters in the choice of visualization techniques based on grounded theory;Gaussian mixture background model with shadow information;an off-line Persian handwritten forgery detection method;partition iterated function radiographs image enhancement for fish bone detection;approximation of 3D data with piecewise series expansions for surface inspection;adequate 3D visualization of remotely sensed ice shelf and sea surface temperature data;and a visual analysis tool for amplifying story generation cycle.
This paper describes initial steps to leverage accelerators, such as GPUs, in ab initio nuclear physics calculations. Specifically, parallel nuclear structure calculations performed by the MFDn package are considered ...
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The proceedings contain 27 papers. The special focus in this conference is on Software Process Improvement and Capability Determination. The topics include: Safety as a process quality characteristic;derivation of gre...
ISBN:
(纸本)9783642382406
The proceedings contain 27 papers. The special focus in this conference is on Software Process Improvement and Capability Determination. The topics include: Safety as a process quality characteristic;derivation of green metrics for software;a process assessment model for security assurance of networked medical devices;the development and current status of medi SPICE;an improvement of process reference model design and validation using business process management;assessing software product management capability;a case study on the need to consider personality types for software team formation;assessment of agile maturity models;agile software development in system engineering conditions;exploring the impact of IT service management process improvement initiatives;software-mediated process assessment in IT service management;balancing agility and discipline in a medical device software organisation;investigation of traceability within a medical device organization;usage of multiple process assessment models;lessons from a pilot implementation of ISO/IEC 29110 in a group of very small Irish companies;critical design decisions in the development of the standard for process assessment;developing the enterprise SPICE strategy using enterprise SPICE;scorecard based project performance management and parameterized generation of process variants and project-specific operating procedures from business process models.
Compression of 3D dynamic datasets in remote visualization still remains two challenges. One is low time performance due to the grown data and complex computation of compression algorithm. Another is small compression...
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Compression of 3D dynamic datasets in remote visualization still remains two challenges. One is low time performance due to the grown data and complex computation of compression algorithm. Another is small compression factor because of dynamic scenes without known equations of their motions. In this paper, we propose a fast and compact compression for 3D dynamic datasets. It accelerates compression with KD-tree construction and node-grid mapping for the dynamic data, which allow parallel rigid body decomposition and merging with disjoint union method. To increase the compression factor, composite rigid body is introduced with consideration of temporary motion consistency among rigid bodies. The results of the experiments show that our algorithm can compress dynamic datasets quickly and obtain high compression factor to reduce limitation of bandwidth.
This paper presents a method that takes advantage of powerful graphics hardware to obtain fully affine-invariant image feature detection and matching. The chosen approach is the accurate, but also very computationally...
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This paper presents a method that takes advantage of powerful graphics hardware to obtain fully affine-invariant image feature detection and matching. The chosen approach is the accurate, but also very computationally expensive, ASIFT algorithm. We have created a CUDA version of this algorithm that is up to 70 times faster than the original implementation, while keeping the algorithm's accuracy close to that of ASIFT. It's matching performance is therefore much better than that of other non-fully affine-invariant algorithms. Also, this approach was adapted to fit the multi-GPU paradigm in order to assess the acceleration potential from modern GPU clusters.
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