Part-Based Visual Tracking via Online Weighted P-N Learning

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="402185.fig.009a" src="https://static.hindawi.com/articles/tswj/volume-2014/402185/figures/402185.fig.009a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b><i> Woman, Subway, Occlusion1,</i> and<i> PersonFloor</i> with heavy occlusion</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="402185.fig.009b" src="https://static.hindawi.com/articles/tswj/volume-2014/402185/figures/402185.fig.009b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b><i> OneLSR</i>,<i> OSOW2cor</i>,<i> Juice, </i>and<i> Cup </i>with scale variation</td></tr></table></td></tr><tr class="fig-image" id="c"><td><img alt="402185.fig.009c" src="https://static.hindawi.com/articles/tswj/volume-2014/402185/figures/402185.fig.009c.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(c) </b><i> Jumping</i>,<i> Lemming, </i>and<i> Deer </i>with fast motion and motion blur</td></tr></table></td></tr><tr class="fig-image" id="d"><td><img alt="402185.fig.009d" src="https://static.hindawi.com/articles/tswj/volume-2014/402185/figures/402185.fig.009d.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(d) </b><i>DavidIndoor </i>and<i> DavidOutdoor </i>with illumination changes</td></tr></table></td></tr></table>

<table>Tracking results on various challenging sequences.</table>

The Scientific World Journal

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Figure 9

Figure 9: Part-Based Visual Tracking via Online Weighted P-N Learning 