de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

Combining Human Perception and Geometric Restrictions for Automatic Pedestrian Detection

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83848

Castrillón-Santana,  M
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84291

Vuong,  QC
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

Locator
There are no locators available
Fulltext (public)
There are no public fulltexts available
Supplementary Material (public)
There is no public supplementary material available
Citation

Castrillón-Santana, M., & Vuong, Q. (2006). Combining Human Perception and Geometric Restrictions for Automatic Pedestrian Detection. Current Topics in Artificial Intelligence: 11th Conference of the Spanish Association for Artificial Intelligence (CAEPIA 2005), 163-170.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-CFD1-A
Abstract
Automatic detection systems do not perform as well as human observers, even on simple detection tasks. A potential solution to this problem is training vision systems on appropriate regions of interests (ROIs), in contrast to training on predefined and arbitrarily selected regions. Here we focus on detecting pedestrians in static scenes. Our aim is to answer the following question: Can automatic vision systems for pedestrian detection be improved by training them on perceptually-defined ROIs?