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International Symposium on Visual Computing

ISVC 2016: Advances in Visual Computing pp 125–135Cite as

Detecting Tracking Failures from Correlation Response Maps

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10072))

Abstract

Tracking methods based on correlation filters have gained popularity in recent years due to their robustness to rotations, occlusions, and other challenging aspects of visual tracking. Such methods generate a confidence or response map which is used to estimate the new location of the tracked target. By examining the features of this map, important details about the tracker status can be inferred and compensatory measures can be taken in order to minimize failures. We propose an algorithm that uses the mean and entropy of this response map to prevent bad target model updates caused by problems such as occlusions and motion blur as well as to determine the size of the target search area. Quantitative experiments demonstrate that our method improves success plots over a baseline tracker that does not incorporate our failure detection mechanism.

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Notes

  1. 1.

    Because of implementation difficulties, our evaluation excludes the redTeam sequence and covers only 99 of the original 100 sequences.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Marquette University, 1551 W. Wisconsin Ave, Milwaukee, Wisconsin, 53233, USA

    Ryan Walsh & Henry Medeiros

Authors
  1. Ryan Walsh
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  2. Henry Medeiros
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Corresponding author

Correspondence to Henry Medeiros .

Editor information

Editors and Affiliations

  1. University of Nevada , Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center , Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory , Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute , Reno, Nevada, USA

    Darko Koracin

  5. The Australian National University , O'Malley, Aust Capital Terr, Australia

    Fatih Porikli

  6. Pilot AI Labs , Redwood City, California, USA

    Sandra Skaff

  7. University of Florida , Gainesville, Florida, USA

    Alireza Entezari

  8. Google Inc. , Mountain View, California, USA

    Jianyuan Min

  9. Osaka University , Osaka, Japan

    Daisuke Iwai

  10. The MOVES Institute , Monterey, California, USA

    Amela Sadagic

  11. University of Arizona , Tucson, Arizona, USA

    Carlos Scheidegger

  12. Université Paris-Sud , Orsay, France

    Tobias Isenberg

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© 2016 Springer International Publishing AG

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Cite this paper

Walsh, R., Medeiros, H. (2016). Detecting Tracking Failures from Correlation Response Maps. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science(), vol 10072. Springer, Cham. https://doi.org/10.1007/978-3-319-50835-1_12

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  • DOI: https://doi.org/10.1007/978-3-319-50835-1_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50834-4

  • Online ISBN: 978-3-319-50835-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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