Gerhard Rigoll (Volume ed.)

Pattern Recognition

30th DAGM Symposium Munich, Germany, June 10-13, 2008 Proceedings
Herausgegeben:Rigoll, Gerhard

• Broschiertes Buch

Produktbeschreibung

This book constitutes the refereed proceedings of the 30th Symposium of the German Association for Pattern Recognition, DAGM 2008, held in Munich, Germany, in June 2008. The 53 revised full papers were carefully reviewed and selected from 136 submissions. The papers are organized in topical sections on learning and classification, tracking, medical image processing and segmentation, audio, speech and handwriting recognition, multiview geometry and 3D-reconstruction, motion and matching, and image analysis.

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Produktdetails

• Lecture Notes in Computer Science 5096
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 12279227, 978-3-540-69320-8
• 2008
• Seitenzahl: 556
• Erscheinungstermin: 30. Mai 2008
• Englisch
• Abmessung: 235mm x 155mm x 30mm
• Gewicht: 842g
• ISBN-13: 9783540693208
• ISBN-10: 3540693203
• Artikelnr.: 23898138

Autorenporträt

Gerhard Rigoll studierte an der Universität Stuttgart Technische Kybernetik und war danach am Fraunhofer-Institut (IAO) in Stuttgart tätig. Er promovierte 1986 im Bereich der automatischen Spracherkennung und schloss seine Habilitation für das Fach Mensch-Maschine-Kommunikation 1991 in Stuttgart ab. Von 1986 - 88 war er Postdoctoral Fellow am IBM Thomas Watson Research Center in Yorktown Heights/USA und von 1991-93 Gastwissenschaftler bei den NTT Human Interface Laboratories in Tokio/Japan. Danach war er Universitätsprofessor für Technische Informatik in Duisburg und ist seit 2002 Ordinarius für Mensch-Maschine-Kommunikation an der TU München. Er ist Autor und Co-Autor von mehr als 400 Publikationen in allen Bereichen der multimodalen Mensch-Maschine-Kommunikation und Mustererkennung und aktiv als Mitglied, Gutachter und Editor in vielen nationalen und internationalen wissenschaftlichen Gremien und Verbänden.

Inhaltsangabe

Learning and Classification.
MAP
Inference for Highly
Connected Graphs with DC
Programming.
Approximate Parameter Learning in Conditional Random Fields: An Empirical Investigation.
Simple Incremental One
Class Support Vector Classification.
A Multiple Kernel Learning Approach to Joint Multi
class Object Detection.
Fast Generalized Belief Propagation for MAP Estimation on 2D and 3D Grid
Like Markov Random Fields.
Boosting for Model
Based Data Clustering.
Improving the Run
Time Performance of Multi
class Support Vector Machines.
Sliding
Windows for Rapid Object Class Localization: A Parallel Technique.
A Performance Evaluation of Single and Multi
feature People Detection.
Tracking.
Model
Based Motion Capture for Crash Test Video Analysis.
Efficient Tracking as Linear Program on Weak Binary Classifiers.
A Comparison of Region Detectors for Tracking.
Combining Densely Sampled Form and Motion for Human Action Recognition.
Recognition and Tracking of 3D Objects.
Medical Image Processing and Segmentation.
Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification.
Real
Time Neighborhood Based Disparity Estimation Incorporating Temporal Evidence.
A Novel Approach for Detection of Tubular Objects and Its Application to Medical Image Analysis.
Weakly Supervised Cell Nuclei Detection and Segmentation on Tissue Microarrays of Renal Clear Cell Carcinoma.
A Probabilistic Segmentation Scheme.
Using Eigenvalue Derivatives for Edge Detection in DT
MRI Data.
Space
Time Multi
Resolution Banded Graph
Cut for Fast Segmentation.
Combination of Multiple Segmentations by a Random Walker Approach.
Audio, Speech and Handwriting Recognition.
Automatic Detection of Learnability under Unreliable and Sparse User Feedback.
Novel VQ Designs for Discrete HMM On
Line Handwritten Whiteboard Note Recognition.
Switching Linear Dynamic Models for Noise Robust In
Car Speech Recognition.
Natural Language Understanding by Combining Statistical Methods and Extended Context
Free Grammars.
Multiview Geometry and 3D
Reconstruction.
Photoconsistent Relative Pose Estimation between a PMD 2D3D
Camera and Multiple Intensity Cameras.
Implicit Feedback between Reconstruction and Tracking in a Combined Optimization Approach.
3D Body Scanning in a Mirror Cabinet.
On Sparsity Maximization in Tomographic Particle Image Reconstruction.
Resolution Enhancement of PMD Range Maps.
A Variational Model for the Joint Recovery of the Fundamental Matrix and the Optical Flow.
Motion and Matching.
Decomposition of Quadratic Variational Problems.
A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry.
Optical Rails.
Postprocessing of Optical Flows Via Surface Measures and Motion Inpainting.
An Evolutionary Approach for Learning Motion Class Patterns.
Relative Pose Estimation from Two Circles.
Staying Well Grounded in Markerless Motion Capture.
An Unbiased Second
Order Prior for High
Accuracy Motion Estimation.
Physically Consistent Variational Denoising of Image Fluid Flow Estimates.
Convex Hodge Decomposition of Image Flows.
Image Analysis.
Image Tagging Using PageRank over Bipartite Graphs.
On the Relation between Anisotropic Diffusion and Iterated Adaptive Filtering.
Comparing Local Feature Descriptors in pLSA
Based Image Models.
Example
Based Learning for Single
Image Super
Resolution.
Statistically Optimal Averaging for Image Restoration and Optical Flow Estimation.
Deterministic Defuzzification Based on Spectral Projected Gradient Optimization.
Learning Visual Compound Models from Parallel Image
Text Datasets.
Measuring Plant Root Growth.
A Local Discriminative Model for Background Subtraction.
Perspective Shape from Shading with Non
Lambertian Reflectance.
The Conformal Monogenic Signal.