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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2022.2
- 수록면
- 247 - 256 (10page)
이용수
초록· 키워드
오류제보하기
Visual tracking of selected target objects is fundamental challenging problems in computer vision. Object tracking localize the region of target object with bounding box in the video. We propose a Siam-FPN based custom fully CNN to solve visual tracking problems by regressing the target area in an end-to-end manner. A method of preserving the feature information flow using a feature map connection structure was applied. In this way, information is preserved and emphasized across the network. To regress object region and to classify object, the region proposal network was connected with the Siamese network. The performance of the tracking algorithm was evaluated using the OTB-100 dataset. Success Plot and Precision Plot were used as evaluation matrix. As a result of the experiment, 0.621 in Success Plot and 0.838 in Precision Plot were achieved.
목차
ABSTRACT
1. 서론
2. 관련연구
3. 제안하는 추적 알고리즘
4. 실험 결과
5. 결론
REFERENCE
참고문헌 (20)
참고문헌 신청
S.H. Kim, S.C. Lim, and D.Y. Kim, “Intelligent Intrusion Detection System Featuring a Virtual Fence, Active Intruder Detection, Classification, Tracking, and Action Recognition,” Annals of Nuclear Energy, Vol. 112, pp. 845-855, 2018.
A. Koubâa and B. Qureshi, “DroneTrack: Cloud-Based Real-Time Object Tracking Using Unmanned Aerial Vehicles over the Internet,” IEEE Access, Vol. 6, pp. 13810-13824, 2018.
S.J. Lee and M.C. Lee, “A Vision Based People Tracking and Following for Mobile Robots Using CAMSHIFT and KLT Feature Tracker,” Journal of Korea Multimedia Society, Vol. 17, No. 7, pp. 787-796, 2014.
V.A. Laurense, J.Y. Goh, and J.C. Gerdes, “Path-Tracking for Autonomous Vehicles at the Limit of Friction,” Proceeding of American Control Conference (ACC). IEEE, pp. 5586-5591, 2017.
S.W. Park, S.H. Kim, S.C. Lim, and D.Y. Kim, “Performance Comparison of Commercial and Customized CNN for Detection in Nodular Lung Cancer,” Journal of Korea Multimedia Society, Vol. 23, No. 6, pp. 729-737, 2020.
A. Koubâa and B. Qureshi, “DroneTrack: Cloud-Based Real-Time Object Tracking Using Unmanned Aerial Vehicles over the Internet,” IEEE Access, Vol. 6, pp. 13810-13824, 2018.
S.J. Lee and M.C. Lee, “A Vision Based People Tracking and Following for Mobile Robots Using CAMSHIFT and KLT Feature Tracker,” Journal of Korea Multimedia Society, Vol. 17, No. 7, pp. 787-796, 2014.
V.A. Laurense, J.Y. Goh, and J.C. Gerdes, “Path-Tracking for Autonomous Vehicles at the Limit of Friction,” Proceeding of American Control Conference (ACC). IEEE, pp. 5586-5591, 2017.
S.W. Park, S.H. Kim, S.C. Lim, and D.Y. Kim, “Performance Comparison of Commercial and Customized CNN for Detection in Nodular Lung Cancer,” Journal of Korea Multimedia Society, Vol. 23, No. 6, pp. 729-737, 2020.
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UCI(KEPA) : I410-ECN-0101-2022-004-001088820