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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2023.1
- 수록면
- 17 - 24 (8page)
- DOI
- 10.9717/kmms.2023.26.1.017
이용수
초록· 키워드
오류제보하기
Object tracking is considered a challenging problem due to various environmental changes contained in the video sequence. Object tracking is the use of information given in the first frame to estimate the area and trajectory of a target object in a video sequence. In this paper, we propose an algorithm for object tracking using multi-scale feature maps of Resnet-50 and correlation filters. To accommodate changes in object scale, we create an appearance model using different sized feature maps extracted from each block in the network. In order to maintain the robustness of the appearance model, it is adaptively updated according to the peak value of the response map when occlusion occurs due to obstacles. Experiments result using the OTB2015 dataset showed that the proposed algorithm achieved competitive results on several image attribution such as low resolution, scale variation, occlusion and out of view.
목차
ABSTRACT
1. 서론
2. 관련 연구
3. 제안하는 추적 알고리즘
4. 실험 결과 및 고찰
5. 결론
REFERENCE
참고문헌 (20)
참고문헌 신청
C. Luo, X. Yang, and A. Yuille, “Exploring Simple 3d Multi-Object Tracking for Autonomous Driving,” Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 10488-10497, 2021.
J. Zhu, Y. Lao, and Y. F. Zheng, “Object Tracking in Structured Environments for Video Surveillance Applications,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 20, No. 2, pp. 223-235, 2009.
Q. Wang, F. Chen, W. Xu, and M.H. Yang, “An Experimental Comparison of Online Object-Tracking Algorithms,” Wavelets and Sparsity XIV, Vol. 8138, pp. 311-321, 2011.
H.G. Kiani, A. Fagg, and S. Lucey, “Learning Background-Aware Correlation Filters for Visual Tracking,” Proceedings of the IEEE International Conference on Computer Vision, pp. 1135-1143, 2017.
D.S. Bolme, J.R. Beveridge, B.A. Draper, and Y.M. Lui, “Visual Object Tracking Using Adaptive Correlation Filters,” Proceeding of International Conference on Computer Vision and Pattern Recognition, pp. 2544-2550, 2010.
J. Zhu, Y. Lao, and Y. F. Zheng, “Object Tracking in Structured Environments for Video Surveillance Applications,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 20, No. 2, pp. 223-235, 2009.
Q. Wang, F. Chen, W. Xu, and M.H. Yang, “An Experimental Comparison of Online Object-Tracking Algorithms,” Wavelets and Sparsity XIV, Vol. 8138, pp. 311-321, 2011.
H.G. Kiani, A. Fagg, and S. Lucey, “Learning Background-Aware Correlation Filters for Visual Tracking,” Proceedings of the IEEE International Conference on Computer Vision, pp. 1135-1143, 2017.
D.S. Bolme, J.R. Beveridge, B.A. Draper, and Y.M. Lui, “Visual Object Tracking Using Adaptive Correlation Filters,” Proceeding of International Conference on Computer Vision and Pattern Recognition, pp. 2544-2550, 2010.
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