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International Conference on Advanced Computing, Networking and Security

ADCONS 2011: Advanced Computing, Networking and Security pp 135–145Cite as

Performance Analysis of Pedestrian Detection at Night Time with Different Classifiers

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7135))

Abstract

Pedestrian detection is one of the most important components in driver-assistance system. A performance analysis is done with various classifiers (AdaBoost, Neural Network and SVM) and its behavior of the system is analyzed. As there is large intra-class variability in the pedestrian class, a two stage classifier is used. A review of different pedestrian detection system is done in the paper. Classifiers are arranged based on HAAR-like and HOG features in a coarse to fine manner. Adaboost gives better performance.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Kerala, India

    Praveen Cyriac & Philomina Simon

Authors
  1. Praveen Cyriac
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  2. Philomina Simon
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Editor information

Editors and Affiliations

  1. N.I.T.K., National Institute of Technology Karnataka, Surathkal, 575 025, Mangalore, India

    P. Santhi Thilagam , Alwyn Roshan Pais  & K. Chandrasekaran ,  & 

  2. Indian Institute of Science, 560012, Bangalore, India

    N. Balakrishnan

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© 2012 Springer-Verlag Berlin Heidelberg

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Cyriac, P., Simon, P. (2012). Performance Analysis of Pedestrian Detection at Night Time with Different Classifiers. In: Thilagam, P.S., Pais, A.R., Chandrasekaran, K., Balakrishnan, N. (eds) Advanced Computing, Networking and Security. ADCONS 2011. Lecture Notes in Computer Science, vol 7135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29280-4_15

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  • DOI: https://doi.org/10.1007/978-3-642-29280-4_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29279-8

  • Online ISBN: 978-3-642-29280-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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