Computer Vision - Eccv 2000: 6th European Conference on Computer Vision Dublin, Ireland, June 26 - July 1, 2000, Proceedings, Part II (Paperback, 2000)

Recognition & Modelling I.- Partitioned Sampling, Articulated Objects, and Interface-Quality Hand Tracking.- Real-Time Tracking of Multiple Articulated Structures in Multiple Views.- Pedestrian Detection from a Moving Vehicle.- Vision-Based Guidance and Control of Robots in Projective Space.- Stereoscopic Vision.- A General Method for Unsupervised Segmentation of Images Using a Multiscale Approach.- Image Segmentation by Nonparametric Clustering Based on the Kolmogorov-Smirnov Distance.- Euclidean Group Invariant Computation of Stochastic Completion Fields Using Shiftable-Twistable Functions.- Recognition & Modelling / Stereoscopic Vision / Texture, Shading, & Colour.- Bootstrap Initialization of Nonparametric Texture Models for Tracking.- Quasi-Random Sampling for Condensation.- Tracking Discontinuous Motion Using Bayesian Inference.- Direction Control for an Active Docking Behaviour Based on the Rotational Component of Log-Polar Optic Flow.- The Construction of 3 Dimensional Models Using an Active Computer Vision System.- Significantly Different Textures: A Computational Model of Pre-attentive Texture Segmentation.- Calibrating Parameters of Cost Functionals.- Coupled Geodesic Active Regions for Image Segmentation: A Level Set Approach.- Level Lines as Global Minimizers of Energy Functionals in Image Segmentation.- A Probabilistic Interpretation of the Saliency Network.- Layer Extraction with a Bayesian Model of Shapes.- Model-Based Initialisation for Segmentation.- Statistical Foreground Modelling for Object Localisation.- Nautical Scene Segmentation Using Variable Size Image Windows and Feature Space Reclustering.- A Probabilistic Background Model for Tracking.- On the Performance Characterisation of Image Segmentation Algorithms: A Case Study.- Statistical Significance as an Aid to System Performance Evaluation.- New Algorithms for Controlling Active Contours Shape and Topology.- Motion Segmentation by Tracking Edge Information over Multiple Frames.- Data-Driven Extraction of Curved Intersection Lanemarks from Road Traffic Image Sequences.- Tracking and Characterization of Highly Deformable Cloud Structures.- Calibration.- A Unifying Theory for Central Panoramic Systems and Practical Implications.- Binocular Self-Alignment and Calibration from Planar Scenes.- The Role of Self-Calibration in Euclidean Reconstruction from Two Rotating and Zooming Cameras.- Hand-Eye Calibration from Image Derivatives.- Medical Image Understanding.- Multimodal Elastic Matching of Brain Images.- A Physically-Based Statistical Deformable Model for Brain Image Analysis.- Minimal Paths in 3D Images and Application to Virtual Endoscopy.- Calibration / Medical Image Understanding / Visual Motion.- Kruppa Equation Revisited: Its Renormalization and Degeneracy.- Registration with a Moving Zoom Lens Camera for Augmented Reality Applications.- Calibration of a Moving Camera Using a Planar Pattern: Optimal Computation, Reliability Evaluation, and Stabilization by Model Selection.- Multi-view Constraints between Collineations: Application to Self-Calibration from Unknown Planar Structures.- Stereo Autocalibration from One Plane.- Can We Calibrate a Camera Using an Image of a Flat,Textureless Lambertian Surface?.- Underwater Camera Calibration.- On Weighting and Choosing Constraints for Optimally Reconstructing the Geometry of Image Triplets.- Computation of the Mid-Sagittal Plane in 3D Images of the Brain.- Stochastic Tracking of 3D Human Figures Using 2D Image Motion.- Monocular Perception of Biological Motion - Clutter and Partial Occlusion.- 3-D Motion and Structure from 2-D Motion Causally Integrated over Time: Implementation.- Non-parametric Model for Background Subtraction.- Qualitative Spatiotemporal Analysis Using an Oriented Energy Representation.- Regularised Range Flow.- Visual Encoding of Tilt from Optic Flow: Psychophysics and Computational Modelling.- Visual Motion.- IMPSAC: Synthesis of Importance Sampling and Random Sample Consensus.-