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ACCV
2010
Springer
13 years 2 days ago
A Heuristic Deformable Pedestrian Detection Method
Pedestrian detection is an important application in computer vision. Currently, most pedestrian detection methods focus on learning one or multiple fixed models. These algorithms r...
Yongzhen Huang, Kaiqi Huang, Tieniu Tan
VIIP
2001
13 years 6 months ago
Automatic Tracking of Multiple Pedestrians with Group Formation and Occlusions
This work addresses the problem of automatic tracking of pedestrians observed by a fixed camera in outdoor scenes. Tracking isolated pedestrians is not a difficult task. The chall...
Pedro Mendes Jorge, Arnaldo J. Abrantes, Jorge S. ...
IBPRIA
2009
Springer
13 years 9 months ago
Local Boosted Features for Pedestrian Detection
The present paper addresses pedestrian detection using local boosted features that are learned from a small set of training images. Our contribution is to use two boosting steps. T...
Michael Villamizar, Alberto Sanfeliu, Juan Andrade...
CVPR
2010
IEEE
13 years 10 months ago
Learning Appearance in Virtual Scenarios for Pedestrian Detection
Detecting pedestrians in images is a key functionality to avoid vehicle-to-pedestrian collisions. The most promising detectors rely on appearance-based pedestrian classifiers tra...
Francisco Marin Tur, David Vazquez, David Geronimo...
GECCO
2005
Springer
129views Optimization» more  GECCO 2005»
13 years 10 months ago
Optimization of passenger car design for the mitigation of pedestrian head injury using a genetic algorithm
The problem of pedestrian injury is a significant one throughout the world. In 2001, there were 4724 pedestrian fatalities in Europe and 4882 in the US. Significant advances have ...
Emma Carter, Steve Ebdon, Clive Neal-Sturgess
PRIMA
2007
Springer
13 years 11 months ago
Analysis of Pedestrian Navigation Using Cellular Phones
Navigation services for pedestrians are spreading in recent years. Our approach to provide personal navigation is to build a multiagent system that assigns one guiding agent to eac...
Yuu Nakajima, Takatoshi Oishi, Toru Ishida, Daisuk...