SMAC detects shape deformations and color anomalies in 4D point clouds using Laplace-Beltrami spectral properties without registration or mesh reconstruction.
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UNVERDICTED 3representative citing papers
A joint optimization of neural manifold learning and active-learning-guided Gaussian process regression in latent space outperforms random sampling on synthetic data for complex functions.
A review paper that identifies the outlier sensitivity of classical discriminant analysis and summarizes robust versions based on resistant location and scatter estimators plus diagnostic graphics.
citing papers explorer
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Simultaneous Monitoring of Shape and Surface Color via 4D Point Clouds: A Registration-free Approach
SMAC detects shape deformations and color anomalies in 4D point clouds using Laplace-Beltrami spectral properties without registration or mesh reconstruction.
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Active Learning for Manifold Gaussian Process Regression
A joint optimization of neural manifold learning and active-learning-guided Gaussian process regression in latent space outperforms random sampling on synthetic data for complex functions.
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Robust discriminant analysis
A review paper that identifies the outlier sensitivity of classical discriminant analysis and summarizes robust versions based on resistant location and scatter estimators plus diagnostic graphics.