This paper presents an estimation technique used to represent a parametric curve by a sequence of lines and circular arcs in CNC tool path generation. The advantage of this algorithm is that it can decrease the number of segments required for approximating the curve with the pre-defined tolerance value when compared to the common linearization process. A new combined algorithm also reduces a complexity of existing circular-arc approximation algorithms and can decrease computational time. The main contribution of this paper is a new algorithm provides with smoother feedrate of CNC machining controller due to the corner reduction. The experimental results are provided by the comparison of the original linearization method and this combined linear and circular-arc approximation method.
{"title":"A Combined Linear and Circular-Arc Approximation of Curves for Feedrate Smoothing of CNC Machining","authors":"P. Kaewsaiha, N. Dejdumrong","doi":"10.1109/CGIV.2013.29","DOIUrl":"https://doi.org/10.1109/CGIV.2013.29","url":null,"abstract":"This paper presents an estimation technique used to represent a parametric curve by a sequence of lines and circular arcs in CNC tool path generation. The advantage of this algorithm is that it can decrease the number of segments required for approximating the curve with the pre-defined tolerance value when compared to the common linearization process. A new combined algorithm also reduces a complexity of existing circular-arc approximation algorithms and can decrease computational time. The main contribution of this paper is a new algorithm provides with smoother feedrate of CNC machining controller due to the corner reduction. The experimental results are provided by the comparison of the original linearization method and this combined linear and circular-arc approximation method.","PeriodicalId":342914,"journal":{"name":"2013 10th International Conference Computer Graphics, Imaging and Visualization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129986916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a given handwritten curve will be approximately converted into a Bezier curve. First, a number of sampled points on the given curve are systematically chosen to guarantee that the Bezier curve can be adequately modeled without the loss of curve characteristics. These points are considered to be the Bezier control points. The Progressive-Iterative Approximation (PIA) is then adopted to construct the interpolating curve. Employing PIA algorithm, Bernstein polynomials are selected to be a blending function of PIA so that this interpolating curve will develop a Bezier curve. This technique will avoid the ill-conditioned circumstance because of using Newton/Lagrange polynomials in curve fitting.
{"title":"Approximating Handwritten Curve by Using Progressive-Iterative Approximation","authors":"Taweechai Nuntawisuttiwong, N. Dejdumrong","doi":"10.1109/CGIV.2013.15","DOIUrl":"https://doi.org/10.1109/CGIV.2013.15","url":null,"abstract":"In this paper, a given handwritten curve will be approximately converted into a Bezier curve. First, a number of sampled points on the given curve are systematically chosen to guarantee that the Bezier curve can be adequately modeled without the loss of curve characteristics. These points are considered to be the Bezier control points. The Progressive-Iterative Approximation (PIA) is then adopted to construct the interpolating curve. Employing PIA algorithm, Bernstein polynomials are selected to be a blending function of PIA so that this interpolating curve will develop a Bezier curve. This technique will avoid the ill-conditioned circumstance because of using Newton/Lagrange polynomials in curve fitting.","PeriodicalId":342914,"journal":{"name":"2013 10th International Conference Computer Graphics, Imaging and Visualization","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126224955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Visual Sensitivity analysis has proven its feasibility in data exploration and exposing relationships between the variables in the model. However, it lacks the ability of user direct interaction of outputs. To overcome this drawback for this interdisciplinary field, in this paper we introduce a novel approach of integrating an interactive visualization and a sensitivity analysis method into a visual interactive sensitivity analysis environment. This environment is applied to a property prediction system. The interactive visualization will facilitate user interaction with the sensitivity analysis method to adjust the outputs of the analysis procedure. The results are presented graphically to the non-expert users without the need to a prior knowledge of the sensitivity analysis method being used. Additionally, all the results that the non-expert is presented with, are all compiled together and presented to an expert user for further analysis by means of multidimensional scatter plots.
{"title":"Visual Sensitivity Analysis in Real Estate Prediction System","authors":"Massara Daana, M. Huang","doi":"10.1109/CGIV.2013.25","DOIUrl":"https://doi.org/10.1109/CGIV.2013.25","url":null,"abstract":"Visual Sensitivity analysis has proven its feasibility in data exploration and exposing relationships between the variables in the model. However, it lacks the ability of user direct interaction of outputs. To overcome this drawback for this interdisciplinary field, in this paper we introduce a novel approach of integrating an interactive visualization and a sensitivity analysis method into a visual interactive sensitivity analysis environment. This environment is applied to a property prediction system. The interactive visualization will facilitate user interaction with the sensitivity analysis method to adjust the outputs of the analysis procedure. The results are presented graphically to the non-expert users without the need to a prior knowledge of the sensitivity analysis method being used. Additionally, all the results that the non-expert is presented with, are all compiled together and presented to an expert user for further analysis by means of multidimensional scatter plots.","PeriodicalId":342914,"journal":{"name":"2013 10th International Conference Computer Graphics, Imaging and Visualization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122124715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Clustered graphs have been widely consisted in Graph Drawing to overcome the problem of drawing large (or huge) graphs with thousands, or perhaps millions of nodes. Force-directed algorithm is one of the available approaches to draw such graphs with good layouts. However, the force directed methods are often produce very different layout outcomes based on different clustering algorithms that greatly affect the quality of the final result. In this paper, we propose a 'dummy element' approach for drawing clustered graphs by using the traditional force-directed algorithm. Our approach attempts to maximize the satisfaction of aesthetics in graph drawing. The experimental results shown that our new method can reduce the side effects on choosing different clustering methods and improve the quality of final layouts.
{"title":"Improving the Quality of Clustered Graph Drawing through a Dummy Element Approach","authors":"Jie Hua, M. Huang","doi":"10.1109/CGIV.2013.23","DOIUrl":"https://doi.org/10.1109/CGIV.2013.23","url":null,"abstract":"Clustered graphs have been widely consisted in Graph Drawing to overcome the problem of drawing large (or huge) graphs with thousands, or perhaps millions of nodes. Force-directed algorithm is one of the available approaches to draw such graphs with good layouts. However, the force directed methods are often produce very different layout outcomes based on different clustering algorithms that greatly affect the quality of the final result. In this paper, we propose a 'dummy element' approach for drawing clustered graphs by using the traditional force-directed algorithm. Our approach attempts to maximize the satisfaction of aesthetics in graph drawing. The experimental results shown that our new method can reduce the side effects on choosing different clustering methods and improve the quality of final layouts.","PeriodicalId":342914,"journal":{"name":"2013 10th International Conference Computer Graphics, Imaging and Visualization","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116930889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Data Visualization and Visual Analytics (DVVA) techniques help human to extract essential information and knowledge from large and complex data sets, and then represent them clearly and comprehensively in the graphic format for better understanding. These techniques have been successfully applied in many areas, including the application in computer forensic science. This paper discusses the background, approaches to the visual analysis of typical computer forensic data. Primarily we will look at how visualization techniques can enhance the computer forensics task, and proposes a new model with a set of data attributes for visual analytics of computer forensics.
{"title":"Parallel Coordinates Visualization of Large Data Investigation on HDDs","authors":"Wenbo Wang, M. Huang","doi":"10.1109/CGIV.2013.24","DOIUrl":"https://doi.org/10.1109/CGIV.2013.24","url":null,"abstract":"Data Visualization and Visual Analytics (DVVA) techniques help human to extract essential information and knowledge from large and complex data sets, and then represent them clearly and comprehensively in the graphic format for better understanding. These techniques have been successfully applied in many areas, including the application in computer forensic science. This paper discusses the background, approaches to the visual analysis of typical computer forensic data. Primarily we will look at how visualization techniques can enhance the computer forensics task, and proposes a new model with a set of data attributes for visual analytics of computer forensics.","PeriodicalId":342914,"journal":{"name":"2013 10th International Conference Computer Graphics, Imaging and Visualization","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116939203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rattikarn Jaroensawad, N. Dejdumrong, Somchai Prakancharoen
This paper presents two methodologies for approximating a handwritten curve by a Bézier curve using Chebyshev Polynomials. First, two different featured point selection techniques, are introduced in algorithms 1 and 2. Algorithm 1 uses frequency while algorithm 2 uses the analysis of inflection point. Then, using Chebyshev Polynomials for approximation curve, however a new curve must be adjusted by algorithm 3 because the end points of curve are swing.
{"title":"Efficient Handwritten Curve Approximation by a Bezier Curve Using Chebyshev Polynomials","authors":"Rattikarn Jaroensawad, N. Dejdumrong, Somchai Prakancharoen","doi":"10.1109/CGIV.2013.22","DOIUrl":"https://doi.org/10.1109/CGIV.2013.22","url":null,"abstract":"This paper presents two methodologies for approximating a handwritten curve by a Bézier curve using Chebyshev Polynomials. First, two different featured point selection techniques, are introduced in algorithms 1 and 2. Algorithm 1 uses frequency while algorithm 2 uses the analysis of inflection point. Then, using Chebyshev Polynomials for approximation curve, however a new curve must be adjusted by algorithm 3 because the end points of curve are swing.","PeriodicalId":342914,"journal":{"name":"2013 10th International Conference Computer Graphics, Imaging and Visualization","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123928919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we describe an objective smoothness assessment method for volume data. The metric can predict the extent of the difference in smoothness between a reference model, which may not be of perfect quality, and a distorted version. The proposed metric is based on the wavelet characterization of Besov function spaces. The comparison of Besov norm between two models can resolve the global and local differences in smoothness between them. Experimental results from volume datasets with smoothing and sharpening operations demonstrate its effectiveness. Also, the proposed smoothness index correlates well with human perceived vision when compared with direct volume rendered images.
{"title":"Wavelets-Based Smoothness Metric for Volume Data","authors":"Mong-shu Lee, S. Ueng, Jhih-Jhong Lin","doi":"10.1109/CGIV.2013.20","DOIUrl":"https://doi.org/10.1109/CGIV.2013.20","url":null,"abstract":"In this paper we describe an objective smoothness assessment method for volume data. The metric can predict the extent of the difference in smoothness between a reference model, which may not be of perfect quality, and a distorted version. The proposed metric is based on the wavelet characterization of Besov function spaces. The comparison of Besov norm between two models can resolve the global and local differences in smoothness between them. Experimental results from volume datasets with smoothing and sharpening operations demonstrate its effectiveness. Also, the proposed smoothness index correlates well with human perceived vision when compared with direct volume rendered images.","PeriodicalId":342914,"journal":{"name":"2013 10th International Conference Computer Graphics, Imaging and Visualization","volume":"77 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122838335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a method to convert rational Bézier curves into non-rational Bézier curve. Using the proposed method, a series of points are first sampled from the input rational Bézier curve. Then a Progressive Iterative Approximation algorithm is used to calculate for a non-rational Bézier curve that fits the sampling points. Demonstration of using the proposed algorithm to approximate input rational Bézier curves is illustrated. Experimental results show that using more sampling points provides better approximation. However, rendering a Bézier curve with too many control points is time-consuming. The optimal result should provide good approximation using as less sampling points as possible. Quality of the approximation also depend on positions of sampling points.
{"title":"Conversion of Rational Bezier Curves into Non-rational Bezier Curves Using Progressive Iterative Approximation","authors":"Anchisa Chantakamo, N. Dejdumrong","doi":"10.1109/CGIV.2013.16","DOIUrl":"https://doi.org/10.1109/CGIV.2013.16","url":null,"abstract":"This paper presents a method to convert rational Bézier curves into non-rational Bézier curve. Using the proposed method, a series of points are first sampled from the input rational Bézier curve. Then a Progressive Iterative Approximation algorithm is used to calculate for a non-rational Bézier curve that fits the sampling points. Demonstration of using the proposed algorithm to approximate input rational Bézier curves is illustrated. Experimental results show that using more sampling points provides better approximation. However, rendering a Bézier curve with too many control points is time-consuming. The optimal result should provide good approximation using as less sampling points as possible. Quality of the approximation also depend on positions of sampling points.","PeriodicalId":342914,"journal":{"name":"2013 10th International Conference Computer Graphics, Imaging and Visualization","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116660742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Virtual community simulation has been engaged on extensive research studies with rapid usage of virtual worlds. Realistic interaction with virtual humans is a complex research area in such kind of simulations since significant concern need to be devoted in order to simulate the social interactive phenomena. This research proposes a selection process for user interested virtual humans. The implemented selection techniques proposed to overcome limitations in existing virtual object selection techniques such as memory overhead and cognitive effort over the users. System prototype is integrated with multimodal interfaces to provide an immersive user experience in human computer interaction. Studying of the users has been conducted to comparatively evaluate proposed selection techniques with ray casting metaphor which is widely presented in games and simulations. Experiment has been conducted in order to evaluate both ideal and walking states of virtual humans. Results of the user study shows the suitability of proposed head oriented metaphors to interact in simulations which are related with virtual humans.
{"title":"Towards Realism: Selection Techniques for Virtual Human Interaction","authors":"Dasun Gunasekara, P. Wimalaratne","doi":"10.1109/CGIV.2013.28","DOIUrl":"https://doi.org/10.1109/CGIV.2013.28","url":null,"abstract":"Virtual community simulation has been engaged on extensive research studies with rapid usage of virtual worlds. Realistic interaction with virtual humans is a complex research area in such kind of simulations since significant concern need to be devoted in order to simulate the social interactive phenomena. This research proposes a selection process for user interested virtual humans. The implemented selection techniques proposed to overcome limitations in existing virtual object selection techniques such as memory overhead and cognitive effort over the users. System prototype is integrated with multimodal interfaces to provide an immersive user experience in human computer interaction. Studying of the users has been conducted to comparatively evaluate proposed selection techniques with ray casting metaphor which is widely presented in games and simulations. Experiment has been conducted in order to evaluate both ideal and walking states of virtual humans. Results of the user study shows the suitability of proposed head oriented metaphors to interact in simulations which are related with virtual humans.","PeriodicalId":342914,"journal":{"name":"2013 10th International Conference Computer Graphics, Imaging and Visualization","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126410084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work primarily aims at introducing an algorithm for surface construction in conjunction with hybrid Growing Grid network and Evolutionary Algorithm, called Growing Grid-Evolutionary network. The process of surface construction primarily consists of two main steps namely: parameterization and surface fitting. The application of growing grid network is implemented at the parameterization phase; meanwhile the evolutionary algorithm has been used to optimally fit the surfaces through the Non Uniform Relational B-Spline (NURBS) method. Various graphical data are used in the experiment including the free-form objects, parabola, and mask. In order to validate the proposed algorithm, we conduct an error analysis for each step of parameterization and surface fitting by comparing the surface images generated with the original surfaces. Experimental results show that the proposed growing grid-evolutionary network has successfully generated surfaces that resemble the original surfaces and enhance its performance.
{"title":"Growing Grid-Evolutionary Algorithm for Surface Reconstruction","authors":"P. Pandunata, F. Forkan, S. Shamsuddin","doi":"10.1109/CGIV.2013.35","DOIUrl":"https://doi.org/10.1109/CGIV.2013.35","url":null,"abstract":"This work primarily aims at introducing an algorithm for surface construction in conjunction with hybrid Growing Grid network and Evolutionary Algorithm, called Growing Grid-Evolutionary network. The process of surface construction primarily consists of two main steps namely: parameterization and surface fitting. The application of growing grid network is implemented at the parameterization phase; meanwhile the evolutionary algorithm has been used to optimally fit the surfaces through the Non Uniform Relational B-Spline (NURBS) method. Various graphical data are used in the experiment including the free-form objects, parabola, and mask. In order to validate the proposed algorithm, we conduct an error analysis for each step of parameterization and surface fitting by comparing the surface images generated with the original surfaces. Experimental results show that the proposed growing grid-evolutionary network has successfully generated surfaces that resemble the original surfaces and enhance its performance.","PeriodicalId":342914,"journal":{"name":"2013 10th International Conference Computer Graphics, Imaging and Visualization","volume":"66 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131019036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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