Pattern Recognition

1. Poster Session 2

   1. Using Landmarks as a Deformation Prior for Hybrid Image Registration

      • Marcel Lüthi, Christoph Jud, Thomas Vetter

      Pages 196-205

   2. Improving Denoising Algorithms via a Multi-scale Meta-procedure

      • Harold Christopher Burger, Stefan Harmeling

      Pages 206-215

2. Adverse Vision Conditions Challenge

   1. Assessment of Visibility Quality in Adverse Weather and Illumination Conditions

      • Andrzej Śluzek, Mariusz Paradowski

      Pages 216-225

   2. Robust Point Matching in HDRI through Estimation of Illumination Distribution

      • Yan Cui, Alain Pagani, Didier Stricker

      Pages 226-235

   3. Illumination-Robust Dense Optical Flow Using Census Signatures

      • Thomas Müller, Clemens Rabe, Jens Rannacher, Uwe Franke, Rudolf Mester

      Pages 236-245

   4. Efficient Stereo and Optical Flow with Robust Similarity Measures

      • Christian Unger, Eric Wahl, Slobodan Ilic

      Pages 246-255

3. Shape and Matching

   1. Shape- and Pose-Invariant Correspondences Using Probabilistic Geodesic Surface Embedding

      • Aggeliki Tsoli, Michael J. Black

      Pages 256-265

   2. Dense 3D Reconstruction of Symmetric Scenes from a Single Image

      • Kevin Köser, Christopher Zach, Marc Pollefeys

      Pages 266-275

   3. Fingerprints for Machines – Characterization and Optical Identification of Grinding Imprints

      • Ralf Dragon, Tobias Mörke, Bodo Rosenhahn, Jörn Ostermann

      Pages 276-285

   4. Efficient and Robust Alignment of Unsynchronized Video Sequences

      • Georgios D. Evangelidis, Christian Bauckhage

      Pages 286-295

4. Segmentation and Early Vision

   1. Time-Consistent Foreground Segmentation of Dynamic Content from Color and Depth Video

      • Anatol Frick, Markus Franke, Reinhard Koch

      Pages 296-305

   2. Channel Coding for Joint Colour and Depth Segmentation

      • Marcus Wallenberg, Michael Felsberg, Per-Erik Forssén, Babette Dellen

      Pages 306-315

   3. Simultaneous Interpolation and Deconvolution Model for the 3-D Reconstruction of Cell Images

      • Ahmed Elhayek, Martin Welk, Joachim Weickert

      Pages 316-325

   4. Steerable Deconvolution Feature Detection as an Inverse Problem

      • Marco Reisert, Henrik Skibbe

      Pages 326-335

5. Robot Vision

   1. Probabilistic Object Models for Pose Estimation in 2D Images

      • Damien Teney, Justus Piater

      Pages 336-345

   2. Fusion of Audio- and Visual Cues for Real-Life Emotional Human Robot Interaction

      • Ahmad Rabie, Uwe Handmann

      Pages 346-355

6. Machine Learning

   1. Training of Sparsely Connected MLPs

      • Markus Thom, Roland Schweiger, Günther Palm

      Pages 356-365

   2. Minimizing Calibration Time for Brain Reading

      • Jan Hendrik Metzen, Su Kyoung Kim, Elsa Andrea Kirchner

      Pages 366-375

   3. Agnostic Domain Adaptation

      • Alexander Vezhnevets, Joachim M. Buhmann

      Pages 376-385

7. Motion

   1. Will the Pedestrian Cross? Probabilistic Path Prediction Based on Learned Motion Features

      • Christoph G. Keller, Christoph Hermes, Dariu M. Gavrila

      Pages 386-395

This book constitutes the refereed proceedings of the 33rd Symposium of the German Association for Pattern Recognition, DAGM 2011, held in Frankfurt/Main, Germany, in August/September 2011. The 20 revised full papers and 22 revised poster papers were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections on object recognition, adverse vision conditions challenge, shape and matching, segmentation and early vision, robot vision, machine learning, and motion. The volume also includes the young researcher's forum, a section where a carefully jury-selected ensemble of young researchers present their Master thesis work.

• 3D reconstruction
• computer vision
• feature detection
• object detection
• object tracking
• scene analysis
• stereo vision
• algorithm analysis and problem complexity

• Visual Sensorics and Information Processing Lab, Johann-Wolfgang Goethe University, Frankfurt/Main, Germany

  Rudolf Mester

• Computer Vision Laboratory, Linköping University, Linköping, Sweden

  Michael Felsberg

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