Predicting Pedestrian Counts for Crossing Scenario Based on Fused Infrared-Visual Videos

<table class="fixed-width table-group" id="tab5"><tr><td><table class="table"><colgroup><col style="width:4.77em"/><col style="width:6.27em"/><col style="width:7.48em"/></colgroup><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left"><b>Number</b></td><td class="align_center"><b>Total time/s</b></td><td class="align_center"><b>Average time/s</b></td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left"><b>1</b></td><td class="align_center">1.6985</td><td class="align_center">0.0167</td></tr><tr><td class="align_left" colspan="3"><hr/></td></tr><tr><td class="align_left"><b>2</b></td><td class="align_center">1.7535</td><td class="align_center">0.0172</td></tr><tr><td class="align_left" colspan="3"><hr/></td></tr><tr><td class="align_left"><b>3</b></td><td class="align_center">1.6967</td><td class="align_center">0.0166</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>The efficiency of background update.</div>

Journal of Advanced Transportation

tab5

Table 5

Table 5: Predicting Pedestrian Counts for Crossing Scenario Based on Fused Infrared-Visual Videos 