ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술지 Pedestrian Detection with Minimal False Positives per Color-Thermal Image
Cited 4 time in scopus Download 4 time Share share facebook twitter linkedin kakaostory
저자
마수드, 박미룡
발행일
201702
출처
The Arabian Journal for Science and Engineering, v.42 no.8, pp.3207-3219
ISSN
2193-567X
출판사
King Fahd University of Petroleum & Minerals
DOI
https://dx.doi.org/10.1007/s13369-017-2424-3
협약과제
17ZD1200, 상황인지 스마트카 퓨전 플랫폼 개발 및 지역 부품업체 지원사업, 박미룡
초록
This research is based on aggregate channel features utilized for pedestrian detection, and the main focus is to investigate a simple way to reduce the number of false positives per image. The importance of this will be to increase the accuracy of the detector by removing the excessive number of false positives while maintaining the missing rate as low as possible. To omit such unwanted false positives, we utilized an image categorization method for day and night images in order to minimize the misclassification rate. Furthermore, the best extension of the aggregate channel features method was analyzed and is recommended as a base detector. As a result, a night-time pre-trained pedestrian detector is only applied to night images, and a daytime detector is applied to daytime images. Thus, a large number of false positives are avoided while the missing rate is greatly reduced.
KSP 제안 키워드
Aggregate channel features, False positive, Misclassification rate, Missing rate, Night images, Night-time, Thermal image, image categorization, pedestrian detection