Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Topology preserving and controlled topology simplifying multiresolution isosurface extraction
Proceedings of the conference on Visualization '00
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Predictor-Corrector Technique for Visualizing Unsteady Flow
IEEE Transactions on Visualization and Computer Graphics
Tracking and Visualizing Turbulent 3D Features
IEEE Transactions on Visualization and Computer Graphics
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Mean Shift Based Clustering in High Dimensions: A Texture Classification Example
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
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A novel cubic-order algorithm for approximating principal direction vectors
ACM Transactions on Graphics (TOG)
Visualization Handbook
Time-varying reeb graphs for continuous space-time data
SCG '04 Proceedings of the twentieth annual symposium on Computational geometry
Action synopsis: pose selection and illustration
ACM SIGGRAPH 2005 Papers
Volume Tracking Using Higher Dimensional Isosurfacing
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
IEEE Transactions on Visualization and Computer Graphics
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Visualization and exploration of time-varying medical image data sets
GI '07 Proceedings of Graphics Interface 2007
A 3-dimensional sift descriptor and its application to action recognition
Proceedings of the 15th international conference on Multimedia
Texture-based feature tracking for effective time-varying data visualization
IEEE Transactions on Visualization and Computer Graphics
Sequential Document Visualization
IEEE Transactions on Visualization and Computer Graphics
Visual Methods for Analyzing Time-Oriented Data
IEEE Transactions on Visualization and Computer Graphics
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Multiscale Time Activity Data Exploration via Temporal Clustering Visualization Spreadsheet
IEEE Transactions on Visualization and Computer Graphics
Importance-Driven Time-Varying Data Visualization
IEEE Transactions on Visualization and Computer Graphics
Texture-based Transfer Functions for Direct Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
Correlation study of time-varying multivariate climate data sets
PACIFICVIS '09 Proceedings of the 2009 IEEE Pacific Visualization Symposium
Case Study on Visualizing Hurricanes Using Illustration-Inspired Techniques
IEEE Transactions on Visualization and Computer Graphics
Visualization and Exploration of Temporal Trend Relationships in Multivariate Time-Varying Data
IEEE Transactions on Visualization and Computer Graphics
n-SIFT: n-dimensional scale invariant feature transform
IEEE Transactions on Image Processing
Visual exploration of time-series data with shape space projections
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
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This paper presents a time line visualization approach, which allows users to study temporal relationships through encoding their interested data properties to time lines with different shapes and locations. Specifically, our approach extracts key data features as virtual words and uses them to encode various data properties. The distributions of virtual words across time are further applied to study various temporal relationships by generating time lines, which renders sampled time steps as points and temporal sequence as a line. Our approach consists of the three following components. First, we select feature points and collect feature descriptors to build a space of data properties, where virtual words are extracted as representative vectors. Second, the virtual words are applied to characterize feature points and their distribution statistics are used to measure temporal relationships. Third, we demonstrate several methods to visualize time lines flexibly for different data visualization and analysis purposes. We present several case studies to visualize time lines for different data visualization and analysis purposes. Our time line visualization can be used for both summarization and exploration of overall temporal relationships. We demonstrate with examples that time lines can serve as effective exploration, comparison, and visualization tools to study time-varying datasets.