Nonnegative Matrix Factorizations Performing Object Detection and Localization

<table>Output of the on-line detection phase after learning the CarData dataset: query image on the top, (a) NMF, (b) LNMF, (c) NMFsc, and (d) DLPP. The off-line phase has been performed with <svg height="10.9125" id="M269" style="vertical-align:-0.17555pt" version="1.1" viewbox="0 0 49.337502 10.9125" width="49.337502" xmlns="http://www.w3.org/2000/svg">
<g transform="matrix(1.25,0,0,-1.25,0,10.9125)">
<g transform="translate(72,-63.27)">
<text transform="matrix(1,0,0,-1,-71.95,63.5)">
<tspan style="font-size: 12.50px; " x="0" y="0">𝑟</tspan>
<tspan style="font-size: 12.50px; " x="8.5645552" y="0">=</tspan>
<tspan style="font-size: 12.50px; " x="20.604944" y="0">1</tspan>
<tspan style="font-size: 12.50px; " x="26.856443" y="0">1</tspan>
<tspan style="font-size: 12.50px; " x="33.107944" y="0">0</tspan>
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Applied Computational Intelligence and Soft Computing

fig11

Figure 11

Figure 11: Nonnegative Matrix Factorizations Performing Object Detection and Localization 