Novel outline features for pedestrian detection system with thermal images

Chun Fu Lin, Chin Sheng Chen, Wen-Jyi Hwang, Chih Yen Chen, Chi Hung Hwang, Chun Li Chang

研究成果: 雜誌貢獻文章同行評審

21 引文 斯高帕斯(Scopus)


Recently, the need of pedestrian detection at night has gained more and more interest. However, the performance of traditional nighttime pedestrian detection systems remains poor because region of interest (ROI) generation and feature extraction are designed separately. Thus, this paper presents novel thermal imagery algorithms to enhance the performance of nighttime pedestrian detection systems. The proposed thermal image pedestrian detection system involves novel outline features, developed from the ROI generation method of pedestrians that are different from traditional features. A three-layer back-propagation feed-forward neural network is used as the classifier. Two databases, the OTCBVS database and our own are used to evaluate the performance of the proposed thermal image pedestrian detection algorithm. Experimental results show that the proposed outline features are effective, and the detection performance of a traditional pedestrian detection system at night is improved.

頁(從 - 到)3440-3450
期刊Pattern Recognition
出版狀態已發佈 - 2015 十一月 1

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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