Monocular SLAM for Visual Odometry: A Full Approach to the Delayed Inverse-Depth Feature Initialization Method

<table>Composite top-view picture for a desktop environment (left plot). Corresponding camera trajectory and map estimations in <svg height="10.325" id="M345" style="vertical-align:-0.0pt" version="1.1" viewbox="0 0 31.775 10.325" width="31.775" xmlns="http://www.w3.org/2000/svg">
<g transform="matrix(1.25,0,0,-1.25,0,10.325)">
<g transform="translate(72,-63.74)">
<text transform="matrix(1,0,0,-1,-71.95,63.79)">
<tspan style="font-size: 12.50px; " x="0" y="0">𝑋</tspan>
<tspan style="font-size: 12.50px; " x="10.615047" y="0">-</tspan>
<tspan style="font-size: 12.50px; " x="14.778546" y="0">𝑍</tspan>
</text>
</g>
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</svg> view after 790 frames (right plot). Observe that both, camera trajectory and scene structure, have been recovered in a satisfactory manner.</table>

Mathematical Problems in Engineering

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Figure 8

Figure 8: Monocular SLAM for Visual Odometry: A Full Approach to the Delayed Inverse-Depth Feature Initialization Method 