An intelligent interface for interactive classification of volume data based on the 2D embedding of the high dimensional feature space

作者：Wang Gui Zhen; Liu Lin; Ye Shuang; Yan Zhi Cheng; Chen Hai Dong; Chen Wei; Yang Jin Song^*

来源：Chinese Journal of Computers, 2011, 34(3): 566-573.

DOI：10.3724/SP.J.1016.2011.00566

• Adjusting parameters
• Data analysis techniques
• Data sets
• Design spaces
• High-dimensional feature space
• Intelligent data
• Intelligent interface
• Interactive classification
• Multi-dimensional histograms
• Multidimensional scaling analysis
• Over segmentation
• Real time performance
• Statistical information
• Volume classification
• Volume data

Conventional volume data classifications use the statistical information of volume data, e.g. the multi-dimensional histogram, to create a design space to allow for interactive selection and exploration. To obtain a satisfactory result, adjusting parameters may be a time-consuming and laborious process because of the indirect workspace (multi-dimensional histograms) and the lack of adequate visual hints about the underlying dataset. This paper presents an intelligent data classification interface by leveraging the newest volume classification and data analysis techniques. The main steps include: (1) an over-segmentation of the dataset in a user-specified high-dimensional feature space; (2) a proximity-preserving 2D embedding of the centroids of the computed classes by means of the multidimensional scaling analysis; (3) intuitive user exploration, classification and visualization based on the two-dimensional embedding. The approach achieves real-time performance, and has been verified by several experiments.

• 出版日期2011
• 单位计算机辅助设计与图形学国家重点实验室; 浙江大学