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Background Subtraction and Kalman Filter Algorithm for Object Tracking

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Book cover Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1035))

Abstract

Today’s world is confronting real issue regarding open security for which visual surveillance framework is required. Object tracking increases loads of enthusiasm for dynamic research in applications, for example, video surveillance, vehicle navigation, video compression and so on. Distinctive strategies are produced for object tracking purpose however that experiences corruption in execution because of occlusion, complex shapes and enlightenments. In this proposed work, discovery of the moving item has been finished utilizing straightforward background subtraction and a Kalman filter algorithm. Following calculation has been completed and attempted on MATLAB 2013a with working system windows. Strategy contrasts and examines different execution measures and different calculations.

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References

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Acknowledgment

The creator might want to express her earnest on account of her cherished and regarded Guide Dr. S. K. Shah for her significant references and steady consolation. Creator appreciatively recognizes her for granting significant fundamental learning of image processing.

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Authors and Affiliations

  1. Sinhgad College of Engineering, Savitribai Phule Pune University, Pune, India

    Shridevi S. Vasekar

  2. Smt. Kashibai Navale College of Engineering, Savitribai Phule Pune University, Pune, India

    Sanjivani K. Shah

Authors
  1. Shridevi S. Vasekar
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  2. Sanjivani K. Shah
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Corresponding author

Correspondence to Shridevi S. Vasekar .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Solapur University, Solapur, India

    Ravindra S. Hegadi

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© 2019 Springer Nature Singapore Pte Ltd.

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Vasekar, S.S., Shah, S.K. (2019). Background Subtraction and Kalman Filter Algorithm for Object Tracking. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1035. Springer, Singapore. https://doi.org/10.1007/978-981-13-9181-1_18

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  • DOI: https://doi.org/10.1007/978-981-13-9181-1_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9180-4

  • Online ISBN: 978-981-13-9181-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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