Moving Object Detection in Dynamic Environment via Weighted Low-Rank Structured Sparse RPCA and Kalman Filtering

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Method</td><td class="align_center">Iteration</td><td class="align_center">Time(s)</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">Our</td><td class="align_center">8</td><td class="align_center">229.388356</td></tr><tr><td class="align_left">RPCA</td><td class="align_center">247</td><td class="align_center">10.127</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Comparison on the number of iterations with the same stop criterion.</div>

Mathematical Problems in Engineering

tab2

Table 2

Table 2: Moving Object Detection in Dynamic Environment via Weighted Low-Rank Structured Sparse RPCA and Kalman Filtering 