A Fast Poisson Multi-Bernoulli Filter for Multiple Target Tracking
Tetsuya Kusumoto, Masaki Yoneda, Takafumi Nishi, Takashi Ogawa · 2022 25th International Conference on Information Fusion (FUSION) · 2022
This paper presents the Poisson Multi-Bernoulli filters for reducing the complexity. This technique is derived based on Poisson Multi-Bernoulli Mixture (PMBM) filters and Poisson Multi-Bernoulli (PMB) filters for multiple target tracking. The complexity of PMB is increased exponentially with the number of propagated Bernoulli components. There are many cases in which this expansion of complexity is an obstacle blocking incorporation into consumer products. FMB dramatically lower the complexity by using approximation for the data association, which is a bottleneck in PMB processing. Also, under conditions in which tracking has a high degree of difficulty and much clutter is generated, FMB showed performance equivalent to PMB.