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Multiview Pedestrian Detection Based on Vector Boosting

  • Cong Hou
  • Haizhou Ai
  • Shihong Lao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4843)

Abstract

In this paper, a multiview pedestrian detection method based on Vector Boosting algorithm is presented. The Extended Histograms of Oriented Gradients (EHOG) features are formed via dominant orientations in which gradient orientations are quantified into several angle scales that divide gradient orientation space into a number of dominant orientations. Blocks of combined rectangles with their dominant orientations constitute the feature pool. The Vector Boosting algorithm is used to learn a tree-structure detector for multiview pedestrian detection based on EHOG features. Further a detector pyramid framework over several pedestrian scales is proposed for better performance. Experimental results are reported to show its high performance.

Keywords

Pedestrian detection Vector Boosting classification 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Cong Hou
    • 1
  • Haizhou Ai
    • 1
  • Shihong Lao
    • 2
  1. 1.Computer Science and Technology Department, Tsinghua University, Beijing 100084China
  2. 2.Sensing and Control Technology Laboratory, Omron Corporation, Kyoto 619-0283Japan

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