Multi scale block histogram of template feature for pedestrian detection

Shaopeng Tang, Satoshi Goto

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

4 Citations (Scopus)

Abstract

In this paper, a feature for human detection from still image is proposed. A multi scale block histogram of template feature (MB-HOT) is developed for human detection by extending the template level in the feature extraction. It integrates gray value information and gradient value information, and reflects relationship of three blocks. The feature is extracted from more macrostructures level and could represent more characteristic of human body. Experiment on INRIA dataset shows that this feature is more discriminative than other features, such as histogram of orientation gradient (HOG). Graphic process unit (GPU) based implementation is proposed to accelerate the calculation of two features, and make it suitable for real time application.

Original languageEnglish
Title of host publicationProceedings - International Conference on Image Processing, ICIP
Pages3493-3496
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong
Duration: 2010 Sep 262010 Sep 29

Other

Other2010 17th IEEE International Conference on Image Processing, ICIP 2010
CityHong Kong
Period10/9/2610/9/29

Keywords

  • Human detection
  • Multi-scale block histogram of template

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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