지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.6 No.5
- 발행연도
- 2017.10
- 수록면
- 309 - 316 (8page)
- DOI
- 10.5573/IEIESPC.2017.6.5.309
이용수
초록· 키워드
오류제보하기
Object detection is very challenging research in the computer vision community, and vehicle detection has become an important issue in various applications, such as unmanned systems and intelligent transportation systems. Most of these applications require fast and accurate vehicle detection. In recent years, it has been proven that correlation filters can find target objects fast and accurately owing to Parseval’s theorem and dense sampling. However, we think that the existing correlation filters have not used all the helpful information. Therefore, we propose a robust and fast vehicle detection method based on an improved correlation filter framework that exploits the additional information from correlation filters. The proposed vehicle detection algorithm consists of five steps: i) training the correlation filter, ii) correlation of input and the trained filter, iii) finding local maxima as vehicle candidates in the correlation output, iv) filtering the candidates by using the shape and sharpness of the maxima, and v) estimation of the location and scale of the vehicles. The proposed algorithm runs fast and accurately, so it can be applied to many other applications, such as object alignment, object detection, and object tracking. We evaluated the proposed algorithm performance by comparing it with the state-of-the-art correlation filter-based methods.
목차
Abstract
1. Introduction
2. Related Work
3. The Proposed Method
4. Experiments
5. Conclusion
References
참고문헌 (23)
참고문헌 신청
Z. Sun, G. Bebis, and R. Miller, “On-road vehicle detection using Gabor filters and support vector machines,” in Proc. IEEE Int. Conf. Digit. Signal Process., Santorini, Greece, pp. 1019?1022, Jul. 2002. Article (CrossRef Link)
J. Wu, X. Zhang, and J. Zhou, “Vehicle detection in static road images with PCA-and-wavelet-based classifier,” in Proc. IEEE Conf. Intell. Transp. Syst., pp. 740?744, Aug. 25?29, 2001. Article (CrossRef Link)
C. Tzomakas and W. Seelen, “Vehicle detection in traffic scenes using shadow,” Inst. Neuroinf., Ruhtuniv., Bochum, Germany, Tech. Rep. 98-06, 1998. Article (CrossRef Link)
A. Lakshmi Ratan,W. E. L. Grimson, andW. M.Wells, “Object detection and localization by dynamic template warping,” Int. J. Comput. Vis., vol. 36, no. 2, pp. 131?148, Feb. 2000. Article (CrossRef Link)
J. C. Rojas and J. D. Crisman, “Vehicle detection in color images,” in Proc. IEEE Conf. Intell. Transp. Syst., pp. 403?408, Nov. 9?11, 1997. Article (CrossRef Link)
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