3D Point Cloud Denoising Using Graph Laplacian Regularization of a Low Dimensional Manifold Model

Keyphrases

• 3D Point Cloud 100%
• Point Cloud Denoising 100%
• Surface Patch 100%
• Low Dimensional Manifold Model 100%
• Graph Laplacian Regularization 100%
• Graph Laplacian Regularizer 100%
• Robustness to Noise 50%
• State-of-the-art Techniques 50%
• Image Patch 50%
• Denoising 50%
• Similar Patches 50%
• Image Data 50%
• Structural Features 50%
• Patch-based 50%
• Inter-patch Distance 50%
• Stability Properties 50%
• Three-dimensional Space 50%
• Graph Spectral 50%
• Spectral Interpretation 50%
• Distance Measure 50%
• Stereo Matching 50%
• Numerical Stability 50%
• Self-similarity 50%
• Light Sensor 50%
• Point Cloud 50%
• Depth Data 50%
• De-noising Scheme 50%
• Acquisition Process 50%
• Continuous Domain 50%
• Viewpoint Image 50%
• Graph Construction 50%
• Signal Representation 50%
• Multiple Viewpoints 50%
• Natural Graphs 50%
• Surface Location 50%
• Patch Manifold 50%
• New Signals 50%
• Object Surface 50%
• Discrete Observations 50%

Computer Science

• Regularization 100%
• Laplace Operator 100%
• de-noising 100%
• Dimensional Manifold 100%
• Point Cloud 100%
• Stereo Matching 25%
• Distance Measure 25%
• Denoising Scheme 25%
• Structural Feature 25%
• Acquisition Process 25%
• Graph Construction 25%
• Signal Representation 25%
• Continuous Domain 25%
• Discrete Observation 25%

Engineering

• Regularization 100%
• Laplace Operator 100%
• Point Cloud 100%
• State-of-the-Art Method 25%
• Image Patch 25%
• Similarity 25%
• Metrics 25%
• Simulation Result 25%
• Denoising Scheme 25%
• Acquired Data 25%
• Stereo Matching 25%
• Discrete Observation 25%
• Signal Representation 25%
• Numerical Stability 25%