TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Visual Object Tracking using Surface Fitting for Scale and Rotation Estimation |
| 영문제목(English Title) |
Visual Object Tracking using Surface Fitting for Scale and Rotation Estimation |
| 저자(Author) |
Yuhao Wang
Jun Ma
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| 원문수록처(Citation) |
VOL 15 NO. 05 PP. 1744 ~ 1760 (2021. 05) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Since correlation filter appeared in the field of object tracking, it plays an increasingly vital role due to its excellent performance. Although many sophisticated trackers have been successfully applied to track the object accurately, very few of them attaches importance to the scale and rotation estimation. In order to address the above limitation, we propose a novel method combined with Fourier-Mellin transform and confidence evaluation strategy for robust object tracking. In the first place, we construct a correlation filter to locate the target object precisely. Then, a log-polar technique is used in the Fourier-Mellin transform to cope with the rotation and scale changes. In order to achieve subpixel accuracy, we come up with an efficient surface fitting mechanism to obtain the optimal calculation result. In addition, we introduce a confidence evaluation strategy modeled on the output response, which can decrease the impact of image noise and perform as a criterion to evaluate the target model stability. Experimental experiments on OTB100 demonstrate that the proposed algorithm achieves superior capability in success plots and precision plots of OPE, which is 10.8% points and 8.6% points than those of KCF. Besides, our method performs favorably against the others in terms of SRE and TRE validation schemes, which shows the superiority of our proposed algorithm in scale and rotation evaluation.
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| 키워드(Keyword) |
Object Tracking
Fourier-Mellin Transform
Confidence Evaluation
Surface Fitting
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| 파일첨부 |
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