Multi-cell multi-Bernoulli tracking method based on fractal measurement model Online publication date: Thu, 07-Apr-2022
by Jihong Zhu; Mingli Lu; Fei Wang
International Journal of Modelling, Identification and Control (IJMIC), Vol. 37, No. 3/4, 2021
Abstract: For detecting and tracking directly from image observations without the need for any separate target detection, a novel multi-cell tracking method based on multi-Bernoulli filter using fractal measurement model is proposed. The Hurst coefficient is one of most important parameters in application of fractal theory. It is used to construct fractal measurement model in this paper, which is estimated by the rescaled range analysis method. The fractal measurement model can offer two advantages for multi-Bernoulli filter. The one is that the measurement model is easy to establish, the other is that the computation of likelihood function is simple. Experiment results show that our proposed method could achieve an accurate and joint estimate of the number of cells and their individual states especially in the case of the number of cell population varying and the cellular morphology changing. Furthermore, it shows equivalent tracking accuracy against other tracking methods.
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