posted by organizer: HassenDrira || 1206 views || tracked by 3 users: [display]

DIFF-CVML 2017 : 3rd International Workshop on DIFFerential Geometry in Computer Vision and Machine Learning (in conjunction with CVPR 2017)

FacebookTwitterLinkedInGoogle

Link: http://www-rech.telecom-lille.fr/diffcvml2017/index.html
 
When Jul 21, 2017 - Jul 21, 2017
Where Honolulu, Hawai
Submission Deadline Apr 10, 2017
Notification Due May 13, 2017
Final Version Due May 19, 2017
 

Call For Papers

Riemannian geometric computing has received a lot of recent interest in the computer vision community. In particular, Riemannian geometric principles can be applied to a variety of difficult computer vision problems including face recognition, activity recognition, object detection, biomedical image analysis, and structure-from-motion to name a few. Besides their nice mathematical formulation, Riemannian computations based on the geometry of underlying manifolds are often faster and more stable than their classical counterparts. Over the past few years, the popularity of Riemannian algorithms has increased several-fold. Some of the mathematical entities that benefit from a geometric analysis include rotation matrices, medial representations, subspace comparisons, symmetric positive-definite matrices, function spaces, and many more. The topics of interest for this workshop include, but are not limited to:
• 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, Covariances, Symmetric positive-definite matrices,
Mixture models.
• Big Data: Dimension-reduction using geometric tools.
• Bayesian Inferences: Nonlinear domains, Computationalsolutions 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.
Original papers related to the topics of interest listed above can be submitted through the workshop webpage. Papers covering theory and/or application areas of computer vision are invited for submission. All papers will be reviewed under the double blind review process. Submitted papers should follow the same formatting style as a CVPR conference paper.

Related Resources

ICCV 2019   International Conference on Computer Vision
IROS 2019   Intelligent RObots and Systems
CAIP 2019   Computer Analysis of Images and Patterns
SMI 2019   Shape Modelling International (SMI) 2019
ISAIR 2019   The 4th International Symposium on Artificial Intelligence and Robotics 2019
IbPRIA 2019   8th Iberian Conference on Pattern Recognition and Image Analysis
EI- ICVISP 2019   2019 3rd International Conference on Vision, Image and Signal Processing (ICVISP 2019)
EI/SCOPUS-CGDIP 2019   2019 3rd International Conference on Computer Graphics and Digital Image Processing
Ei/Scopus-ICVMIP 2019   2019 3rd International Conference on Visual Media Innovation and Production
ICDMML 2019   【ACM ICPS EI SCOPUS】2019 International Conference on Data Mining and Machine Learning