C4.5: programs for machine learning
C4.5: programs for machine learning
Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion
International Journal of Computer Vision
Estimation of parameters and eigenmodes of multivariate autoregressive models
ACM Transactions on Mathematical Software (TOMS)
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
A symbolic representation of time series, with implications for streaming algorithms
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
PaintingClass: interactive construction, visualization and exploration of decision trees
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Axes-based visualizations with radial layouts
Proceedings of the 2004 ACM symposium on Applied computing
Parallel Coordinates: Visual Multidimensional Geometry and Its Applications
Parallel Coordinates: Visual Multidimensional Geometry and Its Applications
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Visualizing and discovering non-trivial patterns in large time series databases
Information Visualization
Line graph explorer: scalable display of line graphs using Focus+Context
Proceedings of the working conference on Advanced visual interfaces
Outlier-Preserving Focus+Context Visualization in Parallel Coordinates
IEEE Transactions on Visualization and Computer Graphics
Using Multivariate Statistics (5th Edition)
Using Multivariate Statistics (5th Edition)
Facial Action Unit Recognition by Exploiting Their Dynamic and Semantic Relationships
IEEE Transactions on Pattern Analysis and Machine Intelligence
LiveRAC: interactive visual exploration of system management time-series data
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Facial expression recognition based on Local Binary Patterns: A comprehensive study
Image and Vision Computing
Continuous Parallel Coordinates
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
Interactive Coordinated Multiple-View Visualization of Biomechanical Motion Data
IEEE Transactions on Visualization and Computer Graphics
Scattering Points in Parallel Coordinates
IEEE Transactions on Visualization and Computer Graphics
Scalable Multi-variate Analytics of Seismic and Satellite-based Observational Data
IEEE Transactions on Visualization and Computer Graphics
Matching Visual Saliency to Confidence in Plots of Uncertain Data
IEEE Transactions on Visualization and Computer Graphics
Pargnostics: Screen-Space Metrics for Parallel Coordinates
IEEE Transactions on Visualization and Computer Graphics
Stacking Graphic Elements to Avoid Over-Plotting
IEEE Transactions on Visualization and Computer Graphics
Computing Accurate Correspondences across Groups of Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Dynamic Facial Expression Analysis and Synthesis With MPEG-4 Facial Animation Parameters
IEEE Transactions on Circuits and Systems for Video Technology
Evaluation of cluster identification performance for different PCP variants
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
Pathline: a tool for comparative functional genomics
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
Visual analysis of multi-joint kinematic data
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
Facial expression recognition in dynamic sequences: An integrated approach
Pattern Recognition
| Hi-index | 0.00 |
Over the past decade, computer scientists and psychologists have made great efforts to collect and analyze facial dynamics data that exhibit different expressions and emotions. Such data is commonly captured as videos and are transformed into feature-based time-series prior to any analysis. However, the analytical tasks, such as expression classification, have been hindered by the lack of understanding of the complex data space and the associated algorithm space. Conventional graph-based time-series visualization is also found inadequate to support such tasks. In this work, we adopt a visual analytics approach by visualizing the correlation between the algorithm space and our goal -- classifying facial dynamics. We transform multiple feature-based time-series for each expression in measurement space to a multi-dimensional representation in parameter space. This enables us to utilize parallel coordinates visualization to gain an understanding of the algorithm space, providing a fast and cost-effective means to support the design of analytical algorithms.