Nonlinear dimensionality reduction with hybrid distance for trajectory representation of dynamic texture

Keyphrases

• Dynamic Texture 100%
• Nonlinear Dimensionality Reduction 100%
• Hybrid Distance 100%
• Trajectory Representation 100%
• Isometric Embedding 50%
• Data Cluster 50%
• Motion Trajectory 33%
• High Dimensional Data Points 33%
• Cluster Graph 33%
• Dimensionality Reduction 16%
• Texture Analysis 16%
• Structure Model 16%
• Motion Analysis 16%
• Novel Algorithm 16%
• Segmentation-based 16%
• Statistical Features 16%
• Statistical Structure 16%
• Video Data 16%
• Low-dimensional Feature Space 16%
• High-dimensional Feature Space 16%
• Graph-based 16%
• Inter-cluster 16%
• Intra-cluster 16%
• Unsupervised Learning 16%
• Motion Character 16%
• Raw Video 16%
• Texture Database 16%
• Feature Model 16%
• Video Content Analysis 16%
• All-pairs 16%
• Classification Basis 16%

Computer Science

• High Dimensional Data 100%
• Dimensionality Reduction 100%
• Dimensional Feature Space 100%
• Content Analysis 50%
• Unsupervised Learning 50%
• Structure Model 50%
• Motion Analysis 50%
• Reduction Algorithm 50%
• Texture Analysis 50%
• Statistical Feature 50%

Engineering

• Dimensionality 100%
• Data Point 100%
• Dimensional Data 66%
• Dimensional Feature Space 66%
• Feature Model 33%
• Statistical Feature 33%
• Graph-Based Cluster 33%