Geometry and Calibration -- 3D Reconstruction Using an n-Layer Heightmap -- Real-Time Dense Geometry from a Handheld Camera -- From Single Cameras to the Camera Network: An Auto-Calibration Framework for Surveillance -- Active Self-calibration of Multi-camera Systems -- Poster Session I -- Optimization on Shape Curves with Application to Specular Stereo -- Unsupervised Facade Segmentation Using Repetitive Patterns -- Image Segmentation with a Statistical Appearance Model and a Generic Mumford-Shah Inspired Outside Model -- Estimating Force Fields of Living Cells – Comparison of Several Regularization Schemes Combined with Automatic Parameter Choice -- Classification of Microorganisms via Raman Spectroscopy Using Gaussian Processes -- Robust Identification of Locally Planar Objects Represented by 2D Point Clouds under Affine Distortions -- Model-Based Recognition of Domino Tiles Using TGraphs -- Slicing the View: Occlusion-Aware View-Based Robot Navigation -- A Contour Matching Algorithm to Reconstruct Ruptured Documents -- Local Structure Analysis by Isotropic Hilbert Transforms -- Complex Motion Models for Simple Optical Flow Estimation -- Tracking People in Broadcast Sports -- A Template-Based Approach for Real-Time Speed-Limit-Sign Recognition on an Embedded System Using GPU Computing -- Inpainting in Multi-image Stereo -- Analysis of Length and Orientation of Microtubules in Wide-Field Fluorescence Microscopy -- Learning Non-stationary System Dynamics Online Using Gaussian Processes -- Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma -- Recognition -- Efficient Object Detection Using Orthogonal NMF Descriptor Hierarchies -- VF-SIFT: Very Fast SIFT Feature Matching -- One-Shot Learning of Object Categories Using Dependent Gaussian Processes -- Learning and Optimization -- Uncertainty Driven Multi-scale Optimization -- The Group-Lasso: ?1,??? Regularization versus ?1,2 Regularization -- Random Fourier Approximations for Skewed Multiplicative Histogram Kernels -- Gaussian Mixture Modeling with Gaussian Process Latent Variable Models -- Applications -- Classification of Swimming Microorganisms Motion Patterns in 4D Digital In-Line Holography Data -- Catheter Tracking: Filter-Based vs. Learning-Based -- Exploiting Redundancy for Aerial Image Fusion Using Convex Optimization -- Poster Session II -- A Convex Approach for Variational Super-Resolution -- Incremental Learning in the Energy Minimisation Framework for Interactive Segmentation -- A Model-Based Approach to the Segmentation of Nasal Cavity and Paranasal Sinus Boundaries -- Wavelet-Based Inpainting for Object Removal from Image Series -- An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM -- N-View Human Silhouette Segmentation in Cluttered, Partially Changing Environments , -- Nugget-Cut: A Segmentation Scheme for Spherically- and Elliptically-Shaped 3D Objects -- Benchmarking Stereo Data (Not the Matching Algorithms) -- Robust Open-Set Face Recognition for Small-Scale Convenience Applications -- Belief Propagation for Improved Color Assessment in Structured Light -- 3D Object Detection Using a Fast Voxel-Wise Local Spherical Fourier Tensor Transformation -- Matte Super-Resolution for Compositing -- An Improved Histogram of Edge Local Orientations for Sketch-Based Image Retrieval -- A Novel Curvature Estimator for Digital Curves and Images -- Local Regression Based Statistical Model Fitting -- Semi-supervised Learning of Edge Filters for Volumetric Image Segmentation -- Motion -- Geometrically Constrained Level Set Tracking for Automotive Applications -- Interactive Motion Segmentation -- On-Line Multi-view Forests for Tracking -- Low-Level Vision and Features -- Probabilistic Multi-class Scene Flow Segmentation for Traffic Scenes -- A Stochastic Evaluation of the Contour Strength -- Incremental Computation of Feature Hierarchies -- From Box Filtering to Fast Explicit Diffusion -- Surfaces and Materials -- High-Resolution Object Deformation Reconstruction with Active Range Camera -- Selection of an Optimal Polyhedral Surface Model Using the Minimum Description Length Principle -- Learning of Optimal Illumination for Material Classification.

This book constitutes the refereed proceedings of the 32nd Symposium of the German Association for Pattern Recognition, DAGM 2010, held in Darmstadt, Germany, in September 2010. The 24 revised full papers and 34 revised poster papers were carefully reviewed and selected from 134 submissions. The papers are organized in topical sections on geometry and calibration, recognition, learning and optimization, applications, motion, low-level vision and features, as well as on surfaces and materials.