This Volume 4553 of the conference proceedings contains 66 papers. Topics discussed include visualization and optimizationtechniques, three dimensional computer vision, evaluation and systems, video and sequential im...
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This Volume 4553 of the conference proceedings contains 66 papers. Topics discussed include visualization and optimizationtechniques, three dimensional computer vision, evaluation and systems, video and sequential image processing and analysis.
Wireless sensor network (WSN) applications sense events in situ and compute results in-network. Their software components should run on platforms with stringent constraints on node resources. To meet these constraints...
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Wireless sensor network (WSN) applications sense events in situ and compute results in-network. Their software components should run on platforms with stringent constraints on node resources. To meet these constraints, developers often design their programs by trial-and-error. Such manual process is time-consuming and error-prone. Based on an existing task view that treats a WSN application as tasks and models resources as constraints, we propose a new component view that associates components with code optimizationtechniques and constraints. We provide a visualization mechanism to help developers select code optimizationtechniques. We also develop algorithms to synthesize components running on nodes, fulfilling the constraints, and thus optimizing their quality. (C) 2009 Elsevier Inc. All rights reserved.
The traditional digital landscape architecture planning (hereinafter referred to as DLAP) system has problems such as long planning time and rough planning details. This article designs a DLAP system using visualizati...
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We present a novel method to create planar visualizations of treelike structures (e.g., blood vessels and airway trees) where the shape of the object is well preserved, allowing for easy recognition by users familiar ...
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We present a novel method to create planar visualizations of treelike structures (e.g., blood vessels and airway trees) where the shape of the object is well preserved, allowing for easy recognition by users familiar with the structures. Based on the extracted skeleton within the treelike object, a radial planar embedding is first obtained such that there are no self-intersections of the skeleton which would have resulted in occlusions in the final view. An optimization procedure which adjusts the angular positions of the skeleton nodes is then used to reconstruct the shape as closely as possible to the original, according to a specified view plane, which thus preserves the global geometric context of the object. Using this shape recovered embedded skeleton, the object surface is then flattened to the plane without occlusions using harmonic mapping. The boundary of the mesh is adjusted during the flattening step to account for regions where the mesh is stretched over concavities. This parameterized surface can then be used either as a map for guidance during endoluminal navigation or directly for interrogation and decision making. Depth cues are provided with a grayscale border to aid in shape understanding. Examples are presented using bronchial trees, cranial and lower limb blood vessels, and upper aorta datasets, and the results are evaluated quantitatively and with a user study.
There exist different reasons for infrastructure providers to think about upcoming changes and necessary adaptations. This paper covers the experiences made during a three-year research project (called SinOptiKom) dur...
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ISBN:
(纸本)9783319604503;9783319604497
There exist different reasons for infrastructure providers to think about upcoming changes and necessary adaptations. This paper covers the experiences made during a three-year research project (called SinOptiKom) during the development of a geographic information system supported tool for analyzing time-dependent infrastructure optimization results. Beside the data preparation and requirements for the successful implementation of such a tool, the resulting design decisions are presented. Examples for the use and combination of common techniques (such as semantic zooming or highlighting) as well as important usability aspects are explained and will greatly support future research in the domain of infrastructure optimization.
In his text Visualizing Data, William Cleveland demonstrates how the aspect ratio of a line chart can affect an analyst's perception of trends in the data. Cleveland proposes an optimization technique for computin...
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In his text Visualizing Data, William Cleveland demonstrates how the aspect ratio of a line chart can affect an analyst's perception of trends in the data. Cleveland proposes an optimization technique for computing the aspect ratio such that the average absolute orientation of line segments in the chart is equal to 45 degrees. This technique, called banking to 45 degrees, is designed to maximize the discriminability of the orientations of the line segments in the chart. In this paper, we revisit this classic result and describe two new extensions. First, we propose alternate optimization criteria designed to further improve the visual perception of line segment orientations. Second, we develop multi-scale banking, a technique that combines spectral analysis with banking to 45 degrees. Our technique automatically identifies trends at various frequency scales and then generates a banked chart for each of these scales. We demonstrate the utility of our techniques in a range of visualization tools and analysis examples.
visualizationtechniques for the decision space of continuous multi-objective optimization problems (MOPs) are rather scarce in research. For long, all techniques focused on global optimality and even for the few avai...
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ISBN:
(纸本)9783030581145;9783030581152
visualizationtechniques for the decision space of continuous multi-objective optimization problems (MOPs) are rather scarce in research. For long, all techniques focused on global optimality and even for the few available landscape visualizations, e.g., cost landscapes, globality is the main criterion. In contrast, the recently proposed gradient field heatmaps (GFHs) emphasize the location and attraction basins of local efficient sets, but ignore the relation of sets in terms of solution quality. In this paper, we propose a new and hybrid visualization technique, which combines the advantages of both approaches in order to represent local and global optimality together within a single visualization. Therefore, we build on the GFH approach but apply a new technique for approximating the location of locally efficient points and using the divergence of the multi-objective gradient vector field as a robust second-order condition. Then, the relative dominance relationship of the determined locally efficient points is used to visualize the complete landscape of the MOP. Augmented by information on the basins of attraction, this Plot of Landscapes with Optimal Trade-offs (PLOT) becomes one of the most informative multi-objective landscape visualizationtechniques available.
Segmentation of medical images is one of the fundamental problems in image processing field. It aims to provide a crucial decision support to physicians. There are several methods to perform segmentation. Hidden Marko...
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ISBN:
(纸本)9781479941032
Segmentation of medical images is one of the fundamental problems in image processing field. It aims to provide a crucial decision support to physicians. There are several methods to perform segmentation. Hidden Markov Random Fields (HMRF) constitutes an elegant way to model the problem of segmentation. This modelling leads to the minimization of an energy function. In this paper we focus on Particles Swarm optimization (PSO) method to solve this optimization problem. The quality of segmentation is evaluated on grounds truths images using the Kappa index. The results show the supremacy of the HMRF-PSO method compared to Kmeans and threshold based techniques.
Algorithms for data visualizations are essential tools for transforming data into useful narratives. Unfortunately, very few visualization algorithms can handle the large datasets of many real-world scenarios. In this...
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ISBN:
(纸本)9781450356183
Algorithms for data visualizations are essential tools for transforming data into useful narratives. Unfortunately, very few visualization algorithms can handle the large datasets of many real-world scenarios. In this study, we address the visualization of these datasets as a Multi-Objective optimization Problem. We propose mQAPViz, a divide-and-conquer multi-objective optimization algorithm to compute large-scale data visualizations. Our method employs the Multi-Objective Quadratic Assignment Problem (mQAP) as the mathematical foundation to solve the visualization task at hand. The algorithm applies advanced sampling techniques originating from the field of machine learning and efficient data structures to scale to millions of data objects. The algorithm allocates objects onto a 2D grid layout. Experimental results on real-world and large datasets demonstrate that mQAPViz is a competitive alternative to existing techniques.
The rapid evolution of data generation and storage techniques allowed many organizations to create large databases and store valuable information. These databases are becoming less exploited even when they hide potent...
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ISBN:
(纸本)9781467389426
The rapid evolution of data generation and storage techniques allowed many organizations to create large databases and store valuable information. These databases are becoming less exploited even when they hide potentially useful knowledge for the organization. The extraction of this buried information inside these voluminous data bases is managed by "Data Mining". In this context, many association rules extraction techniques have been developed, but the process of presentation and evaluations is not efficient and has yet to be improved. Therefore, solving these problems let us give a general solution that uses a 3D visualization engine and optimizationtechniques to reliably display and judge association rules and their belonging to their corresponding classes to give decision makers less room for errors.
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