Implementing agglomerative hierarchic clustering algorithms for use in document retrieval
Information Processing and Management: an International Journal
Algorithms for clustering data
Algorithms for clustering data
Geometric and solid modeling: an introduction
Geometric and solid modeling: an introduction
Visualization of botanical structures and processes using parametric L-systems
Scientific visualization and graphics simulation
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
VIEW: an exploratory molecular visualization system with user-definable interaction sequences
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Glyphs for Visualizing Uncertainty in Vector Fields
IEEE Transactions on Visualization and Computer Graphics
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We present a method to generate glyphs which convey complex information in graphical form. A glyph has a linear geometry which is specified using geometric operations, each represented by characters nested in a string. This format allows several glyph strings to be concatenated, resulting in more complex geometries. We explore automatic generation of a large number of glyphs using a genetic algorithm. To measure the visual distinctness between two glyph geometries, we use the iterative closest point algorithm. We apply these methods to create two different types of representations for biological proteins, transforming the rich data describing their various characteristics into graphical form. The representations are automatically built from a finite set of glyphs, which have been created manually or using the genetic algorithm.