Energy Minimization Methods in Computer Vision and Pattern Recognition: 7th International Conference, EMMCVPR 2009, Bonn, Germany, August 24-27, 2009, Proceedings / Edition 1

Energy Minimization Methods in Computer Vision and Pattern Recognition: 7th International Conference, EMMCVPR 2009, Bonn, Germany, August 24-27, 2009, Proceedings / Edition 1

by Daniel Cremers
     
 

ISBN-10: 3642036406

ISBN-13: 9783642036408

Pub. Date: 09/01/2009

Publisher: Springer Berlin Heidelberg

This book constitutes the refereed proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2009, held in Bonn, Germany in August 2009.

The 18 revised full papers, 18 poster papers and 3 keynote lectures presented were carefully reviewed and selected from 75 submissions. The papers are

Overview

This book constitutes the refereed proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2009, held in Bonn, Germany in August 2009.

The 18 revised full papers, 18 poster papers and 3 keynote lectures presented were carefully reviewed and selected from 75 submissions. The papers are organized in topical sections on discrete optimization and Markov random fields, partial differential equations, segmentation and tracking, shape optimization and registration, inpainting and image denoising, color and texture and statistics and learning.

Product Details

ISBN-13:
9783642036408
Publisher:
Springer Berlin Heidelberg
Publication date:
09/01/2009
Series:
Lecture Notes in Computer Science / Image Processing, Computer Vision, Pattern Recognition, and Graphics Series, #5681
Edition description:
2009
Pages:
494
Product dimensions:
6.10(w) x 9.30(h) x 1.10(d)

Table of Contents

Discrete Optimization and Markov Random Fields.- Multi-label Moves for MRFs with Truncated Convex Priors.- Detection and Segmentation of Independently Moving Objects from Dense Scene Flow.- Efficient Global Minimization for the Multiphase Chan-Vese Model of Image Segmentation.- Bipartite Graph Matching Computation on GPU.- Pose-Invariant Face Matching Using MRF Energy Minimization Framework.- Parallel Hidden Hierarchical Fields for Multi-scale Reconstruction.- General Search Algorithms for Energy Minimization Problems.- Partial Differential Equations.- Complex Diffusion on Scalar and Vector Valued Image Graphs.- A PDE Approach to Coupled Super-Resolution with Non-parametric Motion.- On a Decomposition Model for Optical Flow.- A Schrödinger Wave Equation Approach to the Eikonal Equation: Application to Image Analysis.- Computing the Local Continuity Order of Optical Flow Using Fractional Variational Method.- A Local Normal-Based Region Term for Active Contours.- Segmentation and Tracking.- Hierarchical Pairwise Segmentation Using Dominant Sets and Anisotropic Diffusion Kernels.- Tracking as Segmentation of Spatial-Temporal Volumes by Anisotropic Weighted TV.- Complementary Optic Flow.- Parameter Estimation for Marked Point Processes. Application to Object Extraction from Remote Sensing Images.- Three Dimensional Monocular Human Motion Analysis in End-Effector Space.- Robust Segmentation by Cutting across a Stack of Gamma Transformed Images.- Shape Optimization and Registration.- Integrating the Normal Field of a Surface in the Presence of Discontinuities.- Intrinsic Second-Order Geometric Optimization for Robust Point Set Registration without Correspondence.- Geodesics in Shape Space via Variational Time Discretization.- Image Registration under Varying Illumination: Hyper-Demons Algorithm.- Hierarchical Vibrations: A Structural Decomposition Approach for Image Analysis.- Inpainting and Image Denoising.- Exemplar-Based Interpolation of Sparsely Sampled Images.- A Variational Framework for Non-local Image Inpainting.- Image Filtering Driven by Level Curves.- Color Image Restoration Using Nonlocal Mumford-Shah Regularizers.- Reconstructing Optical Flow Fields by Motion Inpainting.- Color and Texture.- Color Image Segmentation in a Quaternion Framework.- Quaternion-Based Color Image Smoothing Using a Spatially Varying Kernel.- Locally Parallel Textures Modeling with Adapted Hilbert Spaces.- Global Optimal Multiple Object Detection Using the Fusion of Shape and Color Information.- Statistics and Learning.- Human Age Estimation by Metric Learning for Regression Problems.- Clustering-Based Construction of Hidden Markov Models for Generative Kernels.- Boundaries as Contours of Optimal Appearance and Area of Support.

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