Principles and practice of information theory
Principles and practice of information theory
A simple method for computing general position in displaying three-dimensional objects
Computer Vision, Graphics, and Image Processing
Elements of information theory
Elements of information theory
Plenoptic modeling: an image-based rendering system
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Viewpoint entropy: a new tool for obtaining good views of molecules
VISSYM '02 Proceedings of the symposium on Data Visualisation 2002
Viewpoint Selection using Viewpoint Entropy
VMV '01 Proceedings of the Vision Modeling and Visualization Conference 2001
FPV: fast protein visualization using Java 3D™
Proceedings of the 2003 ACM symposium on Applied computing
Fast adaptive selection of best views
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartIII
Dynamic View Selection for Time-Varying Volumes
IEEE Transactions on Visualization and Computer Graphics
A unified information-theoretic framework for viewpoint selection and mesh saliency
ACM Transactions on Applied Perception (TAP)
Automatic blending of multiple perspective views for aesthetic composition
SG'10 Proceedings of the 10th international conference on Smart graphics
Entropy assisted automated terrain navigation using traveling salesman problem
Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
An information-theoretic ambient occlusion
Computational Aesthetics'07 Proceedings of the Third Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
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The investigation of molecular structures often requires the use of graphics software to display different representations of the molecule of interest. Unfortunately, the commonly available visualization software is generally quite complex and requires a high degree of expertise for the user to obtain the desired images. Often, the selection of interesting views implies a considerable time and effort for nonexperienced users. Characterizing the desired properties the users may need is often impossible. In this paper we present a method to automatically determine certain views of molecules that can be used to study their chemical or physical properties. We have used Information Theory's Shannon entropy in order to characterize two kinds of views: views which show most of the structure of a molecule and views which show a low amount of information of an arrangement of molecules. The first ones can be used to study the composition of the molecule, that is to study certain chemical properties. The latter easily show how molecules are ordered in space and therefore are suitable to infer physical properties of compounds, such as resistance. Finally, we also present an adaptive, hardware accelerated algorithm that makes use of the features of graphics cards to make this calculation in realtime. Our method has proven to give good results as in most cases the views generated by our application can completely replace human involvement. For highly complex compounds, they can be either enough, or a good starting point. Often, our application also provides several views that could be missed by the users.