Symmetrical judgment and improvement of CoHOG feature descriptor for pedestrian detection

Hirokatsu Kataoka, Yoshimitsu Aoki

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

2 Citations (Scopus)

Abstract

Pedestrian detection method is the highest priority for "active safety" which prevents traffic accidents before happens. In previous studies, edge orientation based feature descriptors are proposed. Recently, high standard detection algorithm, Co-occurrence Histograms of Oriented Gradients (CoHOG) is proposed. However, this method has miss detection in complicated situation and processing cost is high. We propose symmetrical judgment algorithm and an extended version of CoHOG for high speed and high accuracy pedestrian detection. The effectiveness of the proposed method was proved on pedestrian detection performance test.

Original languageEnglish
Title of host publicationProceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011
Pages536-539
Number of pages4
Publication statusPublished - 2011 Dec 1
Event12th IAPR Conference on Machine Vision Applications, MVA 2011 - Nara, Japan
Duration: 2011 Jun 132011 Jun 15

Publication series

NameProceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

Other

Other12th IAPR Conference on Machine Vision Applications, MVA 2011
CountryJapan
CityNara
Period11/6/1311/6/15

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Kataoka, H., & Aoki, Y. (2011). Symmetrical judgment and improvement of CoHOG feature descriptor for pedestrian detection. In Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011 (pp. 536-539). (Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011).