A Quantitative Analysis on Two RFS-Based Filtering Methods for Multicell Tracking

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="495765.fig.002a" src="https://static.hindawi.com/articles/mpe/volume-2014/495765/figures/495765.fig.002a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>Partial original RGB image sequences</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="495765.fig.002b" src="https://static.hindawi.com/articles/mpe/volume-2014/495765/figures/495765.fig.002b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Partial results of GM-PHD filter</td></tr></table></td></tr><tr class="fig-image" id="c"><td><img alt="495765.fig.002c" src="https://static.hindawi.com/articles/mpe/volume-2014/495765/figures/495765.fig.002c.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(c) </b>Partial results of multi-Bernoulli filter</td></tr></table></td></tr></table>

<table>Tracking partial results of original RGB image sequences, respectively, frame 9, 19, 22, 30, and 35.</table>

Mathematical Problems in Engineering

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Figure 2: A Quantitative Analysis on Two RFS-Based Filtering Methods for Multicell Tracking 