Particle Filter Tracking

Particle Filter Tracking is a sequential Monte Carlo method for visual tracking that recursively estimates the posterior distribution of a target's state by representing it with a set of weighted samples, or particles, propagated over time according to a dynamic model and updated based on observation likelihood.

1.4K

Publications

73.3K

Citations

3.6K

Authors

1.1K

Institutions

Publications per year

2017–2026

249

Authors

3.6K

  1. LM
    Lyudmila Mihaylova

    University of Sheffield, United Kingdom

    17 publications · 774 citations

    15

    h-index

  2. SM
    Simon Maskell

    Qinetiq (United Kingdom), United Kingdom

    13 publications · 12.5K citations

    12

    h-index

  3. AC
    Andrea Cavallaro

    Queen Mary University of London, United Kingdom

    12 publications · 611 citations

    11

    h-index

  4. BR
    Branko Ristić

    Defence Science and Technology Group, Australia

    12 publications · 946 citations

    11

    h-index

  5. SG
    Simon Godsill

    University of Cambridge, United Kingdom

    11 publications · 513 citations

    11

    h-index

1–5 of 3.6K

Venues

  1. 19

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  2. IEEE Transactions on Signal Processing

    19 publications · 13K citations

    19

    h-index

  3. 17

    h-index

  4. 16

    h-index

  5. 15

    h-index

1–5