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Related Experiment Videos

Fast global kernel density mode seeking: applications to localization and tracking.

Chunhua Shen1, Michael J Brooks, Anton van den Hengel

  • 1School of Computer Science, University of Adelaide, SA 5005, Australia. chunhua.shen@nicta.com.au

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|May 12, 2007
PubMed
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This study introduces annealed mean shift (MS) for reliable object tracking. The novel multibandwidth approach converges to the global mode, overcoming limitations of standard MS for large object displacements in videos.

Area of Science:

  • Computer Vision
  • Machine Learning
  • Optimization Algorithms

Background:

  • Mean shift (MS) is a popular technique for object tracking in videos.
  • Standard MS can fail when target displacement is large, as it may converge to a local mode instead of the global mode.
  • This limitation hinders reliable tracking in dynamic scenarios.

Purpose of the Study:

  • To develop a robust object tracking method that overcomes the local mode convergence issue of standard MS.
  • To propose a novel multibandwidth MS procedure that guarantees convergence to the global mode.
  • To introduce an accelerated version for real-time visual tracking applications.

Main Methods:

  • A novel multibandwidth mean shift (MS) procedure, termed annealed MS, is proposed.

Related Experiment Videos

  • This method utilizes a continuation principle and gradually introduces the influence of the global peak.
  • An accelerated version is developed to reduce computational complexity and iterations for convergence.

    • Main Results:

    • The annealed MS procedure converges to the global mode of the density function, irrespective of the initialization point.
    • The algorithm demonstrates reliable and rapid object localization, even when initialized from a distant point.
    • The accelerated version significantly decreases the number of iterations required for convergence.

    Conclusions:

    • The proposed annealed MS algorithm offers a promising solution for reliable and efficient object tracking in videos.
    • It effectively addresses the limitations of standard MS, particularly in scenarios with large target displacements.
    • The accelerated version makes it suitable for real-time visual tracking applications.