Enhanced robust spatial feature selection and correlation filter learning for UAV tracking

Keyphrases

• Background Noise 100%
• L1-norm 100%
• Feature Correlation 100%
• Correlation Filter 100%
• Boundary Effect 100%
• Jointly Sparse 100%
• UAV Tracking 100%
• Background Pixel 100%
• Spatial Feature Selection 100%
• Filter Learning 100%
• Innovative Methods 50%
• Discrimination Power 50%
• UAV 50%
• Selection Mechanism 50%
• Tracking Approach 50%
• Tracking Performance 50%
• Appearance Features 50%
• Tracker 50%
• Norm-based 50%
• Appearance Changes 50%
• Non-Gaussian Noise 50%
• Sparse Feature Selection 50%
• Vehicle Dataset 50%
• Sparse Feature Learning 50%
• 2-norm 50%
• Structured Sparsity 50%
• Discriminative Correlation Filter 50%
• Filter Model 50%
• Spatial Boundaries 50%
• Alternating Direction multiplier Method 50%

Engineering

• Feature Extraction 100%
• Unmanned Aerial Vehicle 100%
• Spatial Feature 100%
• Boundary Effect 66%
• Sparsity 33%
• Non-Gaussian Noise 33%

Computer Science

• Feature Selection 100%
• Boundary Effect 66%
• Sparsity 33%
• Unmanned Aerial Vehicle 33%
• Representation Learning 33%
• Non-Gaussian Noise 33%