Multi-CueOnboardPedestrianDetectionSVM算法Adboost算法.ppt

Multi-Cue Onboard Pedestrian Detection
Haoyu Ren

8/4/2018
Overview
Author information
Abstract
Related algorithm introduction
Paper content
Experimental Result
Conclusion
8/4/2018
Author information(1/4)
Christian Wojek
Education
puter Science, University of Karlsruhe, Germany, 2000-2006
Visiting Student at McGill University, Montreal, Canada, 2004-2005
2006-, PhD Candidate puter Science, TUD
Research Interest
Object Recognition, Scene Understanding, Activity Recognition and Person Tracking
Papers
1 ECCV’08, 2 CVPR’09
8/4/2018
Author information(2/4)
Stefan Walk
Education
Diploma in Physics, Technische Universität Darmstadt, Germany 2007
2007-, PhD Candidate puter Science, TUD
Research Interest
People detection, Detecting from video data (utilizing motion information)
Papers
1 CVPR’09
8/4/2018
Author information(3/4)
Bernt Schiele
Education
PhD: Docteur de l'Institut Polytechnique de Grenoble, France, 1997
MSc's: Diplom-Informatiker, University of Karlsruhe, Germany, 1994,
DEA de l'informatique de l'ENSIMAG, France, 1993
Experience
Assistant Professor, ETH Zurich, Switzerland, 1999-2004
Postdoctoral Associate and Visiting Assistant Professor, MIT and Cambridge, MA, USA, 1997-2000
Visiting researcher at CMU, 1994
8/4/2018
Author information(4/4)
Bernt Schiele
Research Interest
puting, puter interfaces
External Activities
Associate Editor of PAMI, IJCV and IEEE Pervasive
ECCV’08, CVPR’09, ICCV’09, Area Chair
ICCV 2011, Program CoChair
Papers
2 CVPR’09, 2 CVPR’08, 2 ECCV’08, 1 IJCV’08
8/4/2018
Abstract
This paper systematically evaluates different features and classifiers in a sliding-window framework.
Our experiments indicate that incorporating motion information improves detection performance significantly.
bination of multiple plementary feature types can also help improve performance.
The choice of the classifier-bination and several implementation details are crucial to reach best performance.
In contrast to many recent