Self-Learning Facial Emotional Feature Selection Based on Rough Set Theory

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="802932.fig.001a" src="https://static.hindawi.com/articles/mpe/volume-2009/802932/figures/802932.fig.001a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>Relationship between <svg height="15.0875" id="M142" style="vertical-align:-2.3205pt" version="1.1" viewbox="0 0 34.612499 15.0875" width="34.612499" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg></td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="802932.fig.001b" src="https://static.hindawi.com/articles/mpe/volume-2009/802932/figures/802932.fig.001b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Relationship between <svg height="15.0875" id="M144" style="vertical-align:-2.3205pt" version="1.1" viewbox="0 0 62.174999 15.0875" width="62.174999" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,12.138)"><path d="M609 650l-19 -162l-30 -2q2 69 -14 94q-9 18 -28.5 26t-74.5 8h-88q-30 0 -37 -6.5t-12 -36.5l-41 -212h103q48 0 69 5.5t32 19t26 50.5h29l-40 -198h-30q2 58 -11.5 70.5t-85.5 12.5h-99l-30 -167q-17 -87 3 -101q18 -15 111 -15q59 0 89 7t54 27q8 7 15.5 16t16 21.5
l14 20.5t15 23.5t13.5 21.5l29 -10q-52 -129 -71 -163h-500l6 28q66 4 83 17.5t28 73.5l77 409q11 61 -0.5 75.5t-78.5 18.5l10 28h467z" id="x1D438"></path></g><g transform="matrix(.017,-0,0,-.017,10.806,12.138)"><path d="M300 -147l-18 -23q-106 71 -159 185.5t-53 254.5v1q0 139 53 252.5t159 186.5l18 -24q-74 -62 -115.5 -173.5t-41.5 -242.5q0 -130 41.5 -242.5t115.5 -174.5z" id="x28"></path></g><g transform="matrix(.017,-0,0,-.017,16.687,12.138)"><path d="M780 372q0 -191 -178 -297q-128 -75 -335 -75h-250l7 27q61 7 77 22t28 76l77 398q11 62 0 76.5t-77 22.5l6 28h292q164 0 258.5 -67.5t94.5 -210.5zM678 375q0 119 -73 180.5t-201 61.5q-62 0 -82 -13q-17 -7 -25 -53l-80 -427q-8 -47 -4 -62t26 -20q24 -6 80 -6
q166 0 262.5 95t96.5 244z" id="x1D437"></path></g><g transform="matrix(.017,-0,0,-.017,35.046,12.138)"><path d="M162 -163h-61v866h61v-866z" id="x2223"></path></g><g transform="matrix(.017,-0,0,-.017,44.242,12.138)"><path d="M682 629q-1 -16 -1.5 -72t-2.5 -86l-31 -4q-5 92 -51 129t-139 37q-100 0 -177 -49t-116 -125t-39 -162q0 -122 66 -201t182 -79q83 0 137 42.5t112 128.5l26 -15q-12 -31 -42.5 -88t-45.5 -75q-139 -27 -199 -27q-148 0 -243 81.5t-95 226.5q0 173 129.5 274.5
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</svg></td></tr></table></td></tr></table>

<table>Relationship between entropy, condition entropy, and <svg height="7.9499998" id="M141" style="vertical-align:-0.1638pt" version="1.1" viewbox="0 0 7.0999999 7.9499998" width="7.0999999" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,7.675)"><path d="M387 375q0 -16 -17 -31t-29 -15q-9 0 -12 13q-13 74 -80 74q-36 0 -61 -24.5t-25 -56.5t24 -51.5t68 -19.5q33 0 47 2l2 -7l-32 -42q-20 2 -54 2q-45 0 -74 -21.5t-29 -60.5q0 -41 28 -65.5t73 -24.5q78 0 145 67l17 -23q-33 -47 -84.5 -75t-111.5 -28q-70 0 -114.5 35.5
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</svg>.</table>

Mathematical Problems in Engineering

fig1

Figure 1

Figure 1: Self-Learning Facial Emotional Feature Selection Based on Rough Set Theory 