Quadratic Kalman Filter Object Tracking with Moving Pictures

영상 기반의 이차 칼만 필터를 이용한 객체 추적

Park, Sun-Bae;Yoo, Do-Sik

  • Received : 2015.02.03
  • Accepted : 2016.02.19
  • Published : 2016.02.28


In this paper, we propose a novel quadratic Kalman filter based object tracking algorithm using moving pictures. Quadratic Kalman filter, which is introduced recently, has not yet been applied to the problem of 3-dimensional (3-D) object tracking. Since the mapping of a position in 2-D moving pictures into a 3-D world involves non-linear transformation, appropriate algorithm must be chosen for object tracking. In this situation, the quadratic Kalman filter can achieve better accuracy than extended Kalman filter. Under the same conditions, we compare extended Kalman filter, unscented Kalman filter and sequential importance resampling particle filter together with the proposed scheme. In conculsion, the proposed scheme decreases the divergence rate by half compared with the scheme based on extended Kalman filter and improves the accuracy by about 1% in comparison with the one based on unscented Kalman filter.


Kalman filter;Non-linear filtering;Object tracking;Particle filter;Quadratic Kalman filter


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Supported by : 한국연구재단