A Method for Estimating View Transformations from Image Correspondences Based on the Harmony Search Algorithm

<div>A test example where the HS-RANSAC has been applied to estimate a random transformation <svg height="8.79011pt" id="M198" style="vertical-align:-0.04980946pt" version="1.1" viewbox="-0.0498162 -8.7403 10.3168 8.79011" width="10.3168pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M746 650H445V615C520 608 528 602 528 517V370H255V517C255 602 263 608 335 615V650H35V615C112 608 121 602 121 517V133C121 48 112 42 39 35V0H337V35C263 42 255 48 255 133V319H528V133C528 48 520 42 441 35V0H746V35C670 42 662 48 662 132V517C662 602 668 608 746 615V650Z" id="g13-70"></path><glyph.data ascent="1024" descent="-360" horiz-adv-x="783" vert-adv-y="783"></glyph.data></g></svg> considering only the 75% of additional outliers. (a) The first view and (b) the second view, with black squares representing the detected inliers.</div>

Computational Intelligence and Neuroscience

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Figure 3: A Method for Estimating View Transformations from Image Correspondences Based on the Harmony Search Algorithm 