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Vision Tracking: A Survey of the State-of-the-Art

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Abstract

Vision tracking is a well-studied framework in vision computing. Developing a robust visual tracking system is challenging because of the sudden change in object motion, cluttered background, partial occlusion and camera motion. In this study, the state-of-the art visual tracking methods are reviewed and different categories are discussed. The overall visual tracking process is divided into four stages—object initialization, appearance modeling, motion estimation, and object localization. Each of these stages is briefly elaborated and related researches are discussed. A rapid growth of visual tracking algorithms is observed in last few decades. A comprehensive review is reported on different performance metrics to evaluate the efficiency of visual tracking algorithms which might help researchers to identify new avenues in this area. Various application areas of the visual tracking are also discussed at the end of the study.

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Authors and Affiliations

  1. Department of Information Technology, Techno International New Town (Formerly known as Techno India College of Technology), Kolkata, India

    Anjan Dutta, Atreyee Mondal & Nilanjan Dey

  2. A.K. Choudhury School of Information Technology, University of Calcutta, Kolkata, India

    Soumya Sen

  3. Department of Physics, Faculty of Sciences, Univ. “Dunarea de Jos”, Str. Domneasca, nr. 111, 800201, Galati, Romania

    Luminiţa Moraru

  4. Information Technology Department, Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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Dutta, A., Mondal, A., Dey, N. et al. Vision Tracking: A Survey of the State-of-the-Art. SN COMPUT. SCI. 1, 57 (2020). https://doi.org/10.1007/s42979-019-0059-z

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