Computer Vision -- ECCV 2006

Inhaltsverzeichnis

• Energy Minimization.
• Comparison of Energy Minimization Algorithms for Highly Connected Graphs.
• A Comparative Study of Energy Minimization Methods for Markov Random Fields.
• Measuring Uncertainty in Graph Cut Solutions – Efficiently Computing Min-marginal Energies Using Dynamic Graph Cuts.
• Tracking and Motion.
• Tracking Dynamic Near-Regular Texture Under Occlusion and Rapid Movements.
• Simultaneous Object Pose and Velocity Computation Using a Single View from a Rolling Shutter Camera.
• A Theory of Multiple Orientation Estimation.
• Poster Session II.
• Resolution-Aware Fitting of Active Appearance Models to Low Resolution Images.
• High Accuracy Optical Flow Serves 3-D Pose Tracking: Exploiting Contour and Flow Based Constraints.
• Enhancing the Point Feature Tracker by Adaptive Modelling of the Feature Support.
• Tracking Objects Across Cameras by Incrementally Learning Inter-camera Colour Calibration and Patterns of Activity.
• Monocular Tracking of 3D Human Motion with a Coordinated Mixture of Factor Analyzers.
• Multiview Geometry and 3D Reconstruction.
• Balanced Exploration and Exploitation Model Search for Efficient Epipolar Geometry Estimation.
• Shape-from-Silhouette with Two Mirrors and an Uncalibrated Camera.
• Robust and Efficient Photo-Consistency Estimation for Volumetric 3D Reconstruction.
• An Affine Invariant of Parallelograms and Its Application to Camera Calibration and 3D Reconstruction.
• Nonrigid Shape and Motion from Multiple Perspective Views.
• 3D Surface Reconstruction Using Graph Cuts with Surface Constraints.
• Statistical Models and Visual Learning.
• Trace Quotient Problems Revisited.
• Learning Nonlinear Manifolds from Time Series.
• Accelerated Convergence Using Dynamic Mean Shift.
• Efficient Belief Propagation with Learned Higher-Order Markov Random Fields.
• Non Linear Temporal Textures Synthesis: A Monte Carlo Approach.
• Low-Level Vision, Image Features.
• Curvature-Preserving Regularization of Multi-valued Images Using PDE’s.
• Higher Order Image Pyramids.
• Image Specific Feature Similarities.
• Coloring Local Feature Extraction.
• Defocus Inpainting.
• Viewpoint Induced Deformation Statistics and the Design of Viewpoint Invariant Features: Singularities and Occlusions.
• Face/Gesture/Action Detection and Recognition.
• Spatio-temporal Embedding for Statistical Face Recognition from Video.
• Super-Resolution of 3D Face.
• Estimating Gaze Direction from Low-Resolution Faces in Video.
• Learning Effective Intrinsic Features to Boost 3D-Based Face Recognition.
• Human Detection Using Oriented Histograms of Flow and Appearance.
• Cyclostationary Processes on Shape Spaces for Gait-Based Recognition.
• Segmentation and Grouping.
• Multiclass Image Labeling with Semidefinite Programming.
• Automatic Image Segmentation by Positioning a Seed.
• Patch-Based Texture Edges and Segmentation.
• Unsupervised Texture Segmentation with Nonparametric Neighborhood Statistics.
• Detecting Symmetry and Symmetric Constellations of Features.
• Discovering Texture Regularity as a Higher-Order Correspondence Problem.
• Object Recognition, Retrieval and Indexing.
• Exploiting Model Similarity for Indexing and Matching to a Large Model Database.
• Shift-Invariant Dynamic Texture Recognition.
• Modeling 3D Objects from Stereo Views and Recognizing Them in Photographs.
• A Boundary-Fragment-Model for Object Detection.
• Region Covariance: A Fast Descriptor for Detection and Classification.
• Segmentation.
• Affine-Invariant Multi-reference Shape Priors for Active Contours.
• Figure/Ground Assignment in Natural Images.
• Background Cut.
• PoseCut: Simultaneous Segmentation and 3D Pose Estimation of Humans Using Dynamic Graph-Cuts.