3rd International Workshop on Diff-CVML: Differential Geometry in Computer Vision and Machine Learning

Main topics of interest

• Shape Representations: Silhouettes, Surfaces, Skeletons, Humans, etc..

• Information Geometry: Fisher-Rao and elastic metrics, Gromov-Wasserstein family, Earth-Mover’s distance, etc.

• Dynamical Systems: Trajectories on manifolds, Rate-invariance, Identification and classification of systems.

• Domain Transfer: Ideas and applications.

• Image/Volume/Trajectory: Spatial and temporal registration & segmentation.

• Manifold-Valued Features: Histograms, Covariance, Symmetric positive-definite matrices, Mixture model.

• Big Data: Dimension-reduction using geometric tools.

• Bayesian Inferences: Nonlinear domains, Computational solutions using differential geometry, Variational approaches.

• Machine Learning Approaches on Nonlinear Feature Spaces: Kernel methods, Boosting, SVM-type classification, Detection and tracking algorithms.

• Functional Data Analysis: Hilbert manifolds, Visualization.

• Applications: Medical analysis, Biometrics, Biology, Environmetrics, Graphics, Activity recognition, Bioinformatics, Pattern recognition, etc.

• Geometry of articulated bodies: Applications to robotics, biomechanics, and motor control.

• Computational topology and applications.