Pattern Recognition

1. Front Matter

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2. Learning and Classification

   1. MAP-Inference for Highly-Connected Graphs with DC-Programming

      • Jörg Kappes, Christoph Schnörr

      Pages 1-10

   2. Approximate Parameter Learning in Conditional Random Fields: An Empirical Investigation

      • Filip Korč, Wolfgang Förstner

      Pages 11-20

   3. Simple Incremental One-Class Support Vector Classification

      • Kai Labusch, Fabian Timm, Thomas Martinetz

      Pages 21-30

   4. A Multiple Kernel Learning Approach to Joint Multi-class Object Detection

      • Christoph H. Lampert, Matthew B. Blaschko

      Pages 31-40

   5. Fast Generalized Belief Propagation for MAP Estimation on 2D and 3D Grid-Like Markov Random Fields

      • Kersten Petersen, Janis Fehr, Hans Burkhardt

      Pages 41-50

   6. Boosting for Model-Based Data Clustering

      • Amir Saffari, Horst Bischof

      Pages 51-60

   7. Improving the Run-Time Performance of Multi-class Support Vector Machines

      • Andrey Sluzhivoy, Josef Pauli, Volker Rölke, Anastasia Noglik

      Pages 61-70

   8. Sliding-Windows for Rapid Object Class Localization: A Parallel Technique

      • Christian Wojek, Gyuri Dorkó, André Schulz, Bernt Schiele

      Pages 71-81

   9. A Performance Evaluation of Single and Multi-feature People Detection

      • Christian Wojek, Bernt Schiele

      Pages 82-91

3. Tracking

   1. Model-Based Motion Capture for Crash Test Video Analysis

      • Juergen Gall, Bodo Rosenhahn, Stefan Gehrig, Hans-Peter Seidel

      Pages 92-101

   2. Efficient Tracking as Linear Program on Weak Binary Classifiers

      • Michael Grabner, Christopher Zach, Horst Bischof

      Pages 102-111

   3. A Comparison of Region Detectors for Tracking

      • Andreas Haja, Steffen Abraham, Bernd Jähne

      Pages 112-121

   4. Combining Densely Sampled Form and Motion for Human Action Recognition

      • Konrad Schindler, Luc van Gool

      Pages 122-131

   5. Recognition and Tracking of 3D Objects

      • Christian Wiedemann, Markus Ulrich, Carsten Steger

      Pages 132-141

4. Medical Image Processing and Segmentation

   1. Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification

      • Björn Andres, Ullrich Köthe, Moritz Helmstaedter, Winfried Denk, Fred A. Hamprecht

      Pages 142-152

   2. Real-Time Neighborhood Based Disparity Estimation Incorporating Temporal Evidence

      • Bogumil Bartczak, Daniel Jung, Reinhard Koch

      Pages 153-162

   3. A Novel Approach for Detection of Tubular Objects and Its Application to Medical Image Analysis

      • Christian Bauer, Horst Bischof

      Pages 163-172

   4. Weakly Supervised Cell Nuclei Detection and Segmentation on Tissue Microarrays of Renal Clear Cell Carcinoma

      • Thomas J. Fuchs, Tilman Lange, Peter J. Wild, Holger Moch, Joachim M. Buhmann

      Pages 173-182

   5. A Probabilistic Segmentation Scheme

      • Dmitrij Schlesinger, Boris Flach

      Pages 183-192

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.

• 3D
• 3D reconstruction
• camera calibration
• classification
• computer vision
• ensemble methods
• feature detection
• feature extraction
• image analysis
• image annotation
• image processing
• image reconstruction
• image segmentation
• image sequences
• pattern recognition

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