Arbitration algorithm of FIR filter and optical flow based on ANFIS for visual object tracking

In Hwan Choi, Jung Min Pak, Choon Ki Ahn, Seung Han Lee, Myo Taeg Lim, Moon Kyou Song

Research output: Contribution to journalArticle

20 Citations (Scopus)


This paper proposes a new visual object tracking algorithm based on an adaptive neuro fuzzy inference system (ANFIS) for arbitration algorithm between a finite impulse response (FIR) filter and optical flow (OF). The proposed algorithm is called ANFIS-based FIR filter and OF arbitration (AFOA). The AFOA operates as an FIR filter for normal situations, keeping the computational cost low, and, when abrupt turns occur, converts to an OF to compensate for the inaccuracy of the FIR filter. An ANFIS-based arbitration algorithm constructs a mapping system from given inputs to an output using fuzzy logic and determines tracking mode of the tracking process between the FIR filter and the OF. The effectiveness of the AFOA algorithm is demonstrated by experiments employed on real-time video clips along with a comparative analysis with the ANFIS-based Kalman filter and OF arbitration (AKOA).

Original languageEnglish
Pages (from-to)338-353
Number of pages16
JournalMeasurement: Journal of the International Measurement Confederation
Publication statusPublished - 2015 Nov 2


  • Adaptive neuro fuzzy inference system (ANFIS)
  • ANFIS-based FIR filter and OF arbitration (AFOA)
  • Finite impulse response (FIR) filter
  • Optical flow
  • Visual object tracking

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Applied Mathematics

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