PETS 2009 Final Programme

Learning from Diasagreements: Discriminative Performance Evaluation
C. Pavlopoulou, D. Martin, S. Yu and H. Jiang, Boston College, MA, USA
An Object Assignment Algorithm for Tracking Performance Evaluation
N. Saunier, T. Sayed and K. Ismail, Department of Civil Engineering, University of British Columbia, Canada
Recurrent Tracking using Manifold Consistency
P. Pan, University of Illinois at Chicago, USA; F. Porikli, Mitsubishi Electric Research Labs, MA, USA; D. Schonfeld, University of Illinois at Chicago, USA

An Overview of the PETS2009 Dataset
J. Ferryman and A. Shahrokni, Computational Vision Group, University of Reading, UK
Video Analysis using Corners Motion Analysis,
A. Albiol, M. J. Silla, A. Albiol and J. M. Mossi, ITEAM Institute, Universidad Politecnica Valencia, Spain
Evaluation of People Tracking, Counting and Density Estimation in Crowded Environments
P. K. Sharma, C. Huang and R. Nevatia, Institute for Robotics and Intelligent Systems, University of Southern California, CA, USA
A Comparison of Multi Hypothesis Kalman Filter and Particle Filter for Multi-Target Tracking
L. Bazzani, Department of Informatics, University of Verona, Italy; D. Bloisi, Department of informatics and Systems, Sapienza University of Rome, Italy; V. Murino, Department of Informatics, Unversity of Verona, Italy.

Evaluation of Probabilistic Occupancy Map People Detection for Surveillance Systems,
J. Berclaz, and P. Fua, Computer Vision Laboratory, EPFL, Switzerland; F. Fleuret, IDIAP Research Institute, artigny, Switzerland; A. Shahrokni and J. Ferryman, Computational Vision Group, University of Reading, UK
Exploring Context to Learn Scene Specific Object Detectors,
S. Stalder, H. Grabner and L. Van Gool, Computer Vision Laboratory, ETH-Zurich, Switzerland.
Markovian Tracking-by-Detection from a Single, Uncalibrated Camera
M. D. Breitenstein, F. Reichlin, B. Leibe, E. Koller-Meier and L. Van Gool, ETH-Zurich, Switzerland.
Probabilistic Multiple People Tracking through Complex Situations
J. Yang and Z. Shi, School of Automation, Northwestern Polytechnical University, Xi'an, China; P. Vela, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA; J. Teizer, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA.

Analysis of Crowded Scenes using Holistic Properties
A. B. Chan, M. Morrow and N. Vasconcelos, Department of Electrical and Computer Engineering, University of California, San Diego, USA.
Supporting Multi Camera Tracking by Monocular Deformable Graph Tracking
N. Lehment, D. Arsic, A. Lyutskanov, B. Schuller and G. Rigoll, Institute fo Human-Machine Communication, Technische Universitat Munchen, Germany.
Statistical Filters for Crowd Image Analysis
A. Utasi, A. Kiss and T. Sziranyi, Computer and Automation Research Institute, Hungarian Academy of Sciences (MTA-SZTAKI), Hungary.
Global Analysis of Motion Vectors for Event Detection in Crowd Scenes
Y. Benabbas, N. Ihaddadene and C. Djeraba, Computer Science Laboratory of Lille (LIFL), France.
Overall Evaluation of the PETS2009 Results
A. Ellis, A. Shahrokni and J. Ferryman, Computational Vision Group, University of Reading, UK