Volume 37, Number 2, April 2019
|Page(s)||323 - 329|
|Published online||05 August 2019|
A New Video Tracking Algorithm Based on Multi-Complementary Features Fusion
School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
2 Science and Technology on Electro-Optic Control Laboratory, Luoyang 471000, China
In order to make full use of the diversity of sample information in the tracking process and improve the generalization ability of the tracker, this paper integrates the object model prediction results on the basis of the Staple algorithm, and applies weighted bands to the simple linearity of different predictive response results in the algorithm. To the uncertainties, a new adaptive response factor graph fusion method with weight coefficients is proposed, which effectively improves the reliability of the video target tracking algorithm. Theoretical analysis and experimental simulation show that the proposed algorithm is more accurate and robust than the classical Staple algorithm, and it maintains high real-time performance.
Key words: correlation filters / object tracking / contour features / adaptive weights / feature fusion
关键字 : 相关滤波 / 目标跟踪 / 轮廓特征 / 自适应权重
© 2019 Journal of Northwestern Polytechnical University. All rights reserved.
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