New efficient speed-up scheme for cascade implementation of SVM classifier

Jeonghyun Baek, Jisu Kim, Junhyuk Hyun, Euntai Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

For intelligent vehicle applications, detecting pedestrian technique must be robust and perform in real time. In pedestrian detection, support vector machine (SVM) is one of the popular classifiers because of its robust performance. In this paper, we propose the new method to implement cascade SVM that enables fast rejection of negative samples. The proposed method is tested with INRIA person dataset and show better rejection performance of negative samples than conventional method.

Original languageEnglish
Title of host publication2015 International Joint Conference on Neural Networks, IJCNN 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479919604, 9781479919604, 9781479919604, 9781479919604
DOIs
Publication statusPublished - 2015 Sep 28
EventInternational Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland
Duration: 2015 Jul 122015 Jul 17

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2015-September

Other

OtherInternational Joint Conference on Neural Networks, IJCNN 2015
CountryIreland
CityKillarney
Period15/7/1215/7/17

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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  • Cite this

    Baek, J., Kim, J., Hyun, J., & Kim, E. (2015). New efficient speed-up scheme for cascade implementation of SVM classifier. In 2015 International Joint Conference on Neural Networks, IJCNN 2015 [7280810] (Proceedings of the International Joint Conference on Neural Networks; Vol. 2015-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2015.7280810