Pedestrian Detection Using a Feature Space Based on Colored Level Lines

  • Pablo Negri
  • Pablo Lotito
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7441)


This work gives the guidelines to develop a pedestrian detection system using a feature space based on colored level lines, called Movement Feature Space (MFS). Besides detecting the movement in the scene, this feature space defines the descriptors used by the classifiers to identify pedestrians. The multi-channel level lines approach has been tested on the HSV color space, which improves the one-channel (gray scale) level lines calculation. Locations hypotheses of pedestrian are performed by a cascade of boosted classifiers. The validation of these regions of interest is carry out by a Support Vector Machine classifier. Results give more than 78.5 % of good detections on urban video sequences.


Feature Space Video Sequence Color Space Level Line Monochromatic Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Pablo Negri
    • 1
    • 2
  • Pablo Lotito
    • 1
    • 3
  1. 1.CONICETCapital FederalArgentina
  2. 2.Instituto de TecnologiaUADECapital FederalArgentina
  3. 3.PLADEMA-UNCPBA, Campus UniversitarioTandilArgentina

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