Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Y. Yagi et al. (Eds.): ACCV 2007, Part I, LNCS 4843, pp. 210219, 2007. Springer-Verlag Berlin Heidelberg 2007
 

Summary: Y. Yagi et al. (Eds.): ACCV 2007, Part I, LNCS 4843, pp. 210219, 2007.
Springer-Verlag Berlin Heidelberg 2007
Multiview Pedestrian Detection Based on Vector Boosting
Cong Hou1
, Haizhou Ai1
, and Shihong Lao2
1
Computer Science and Technology Department, Tsinghua University, Beijing 100084, China
2
Sensing and Control Technology Laboratory, Omron Corporation, Kyoto 619-0283, Japan
ahz@mail.tsinghua.edu.cn
Abstract. In this paper, a multiview pedestrian detection method based on Vec-
tor Boosting algorithm is presented. The Extended Histograms of Oriented Gra-
dients (EHOG) features are formed via dominant orientations in which gradient
orientations are quantified into several angle scales that divide gradient orienta-
tion space into a number of dominant orientations. Blocks of combined rectan-
gles 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.

  

Source: Ai, Haizhou - Department of Computer Science and Technology, Tsinghua University

 

Collections: Computer Technologies and Information Sciences