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Augmented particle samples based optimal convolutional filters for object tracking

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Abstract

This paper presents the augmented particle samples based optimal convolutional filters that preserve the appearance model robustness for object tracking in both temporal and spatial levels. In temporal level, augmented particle samples provided by Laplacian group reverse sparse representation exploit the potential geometrical correlation among the different patches that keep the inherent potential distribution which facilitates the update scheme of appearance model between continuous frames in the particle filtering framework. In spatial level, structural information of multi-scale patches extraction can preserve highly stable attributes that significantly improve the object representation robustness in multi-scenarios. Moreover, the optimal convolutional filters that resulted from laplacian score exploits the coherence of high similarity in both positive and negative sets effectively that can guarantee the template update procedures discriminatively. Experimental results demonstrate that the proposed approach achieves better performance on multiple dynamic scenes.

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Acknowledgments

Sincerely thanks to the professor Nongliang Sun and professor Quanquan Liang, who are crucial for the preparation of the article. This study acknowledges the financial support from the ‘Leading Talents of Shandong University of Science and Technology’, ‘863 project Physical Model Based Dynamic Evolution Technology of Complex Scene’ (2015AA016404), ‘Shandong Province Higher Educational Science and Technology Program’ (J17KA075) and ‘National Nature Science Foundation of China’ (61801270).

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Authors and Affiliations

  1. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, 266590, Shandong Province, People’s Republic of China

    Xiaowei An

  2. College of Electronics and Information Engineering, Shandong University of Science and Technology, Qingdao, 266590, Shandong Province, People’s Republic of China

    Quanquan Liang & Nongliang Sun

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  1. Xiaowei An
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  2. Quanquan Liang
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Correspondence to Quanquan Liang or Nongliang Sun.

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An, X., Liang, Q. & Sun, N. Augmented particle samples based optimal convolutional filters for object tracking. Multimed Tools Appl 80, 4473–4491 (2021). https://doi.org/10.1007/s11042-020-09724-6

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