Accelerating Evolution by Direct Manipulation for Interactive Fashion Design
ICCIMA '01 Proceedings of the Fourth International Conference on Computational Intelligence and Multimedia Applications
Visualizing Time-Series on Spirals
INFOVIS '01 Proceedings of the IEEE Symposium on Information Visualization 2001 (INFOVIS'01)
GGobi: evolving from XGobi into an extensible framework for interactive data visualization
Computational Statistics & Data Analysis - Data visualization
Metacreation: Art and Artificial Life
Metacreation: Art and Artificial Life
Dynamic query tools for time series data sets: timebox widgets for interactive exploration
Information Visualization
Visually mining and monitoring massive time series
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Information Retrieval for Music and Motion
Information Retrieval for Music and Motion
Video browsing by direct manipulation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Multiscale Time Activity Data Exploration via Temporal Clustering Visualization Spreadsheet
IEEE Transactions on Visualization and Computer Graphics
Interactive generation of human animation with deformable motion models
ACM Transactions on Graphics (TOG)
Direct Manipulation Blendshapes
IEEE Computer Graphics and Applications
Dragimation: direct manipulation keyframe timing for performance-based animation
Proceedings of Graphics Interface 2012
Inverse mapping with sensitivity analysis for partial selection in interactive evolution
EvoMUSART'13 Proceedings of the Second international conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
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This paper presents a selection method for use with interactive evolutionary algorithms and sensitivity analysis in spatiotemporal domains. Recent work in the field has made it possible to give feedback to an interactive evolutionary system with a finer granularity than the typical wholesale selection method. This recent development allows the user to drive the evolutionary search in a more precise way by allowing him to select a part of a phenotype to indicate fitness. The method has potential to alleviate the human fatigue bottleneck, so it seems ideally suited for use in domains that vary in both space and time, such as character motion or cloth simulation where evaluation times are long. However no evolutionary interface has been developed yet which will allow for selecting parts of time-varying phenotypes. We present a selection interface that should be fast and intuitive enough to minimize the interaction bottleneck in evolutionary algorithms that receive feedback at the phenotype part level.