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<h1>Week 14-16 </h1>
<h2 class="subheading"> Intrinsic Caliberation of Realsense D435. Processing of the data acquired from the Realsense D435 to determine the centroid of an object and its normal.</h2>
<span class="meta">Posted by
<a href="about.html">Avinash Sen</a>
on April 07, 2020</span>
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<font size="6"><b>Intrinsic Caliberation of Realsense D435</b></font>
<p>In this past two weeks I calibrated the intrinsic parameters of the Realsense and created a launch file that runs all the necessary programs to process and visualize the RGB_D Data acquired
by the Realsense. This launch file already includes the respective .yaml files to calibrate the rgb and the depth of the sensor.
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<p><img class="img-fluid" src="img/int_calib.png" alt=""></p>
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<font size="6"><b>Processing the RGB_D Data</b></font>
<p>Using the recorded rosbag I continued to process the RGB_D data based on the feature points trained by SIFT and FLANN matcher. After that i draw a 2D bounding box around the object trained by finding the corner pixel values of feature points. Then, i was able to determine the centroid of a simple box and its normal.</p>
<p><img src="img/centroid.png" alt="" width="100%" height="100%"/></p>
<p>To do so I started by calculating all the normals of the entire surface and determine the center of it. Afterwards it was necessary to define which of the points of the RGB_D data was closer to the center of the surface and determine its corresponding normal. The visualization of the centroid and its normal is shown below.</p>
<p><img src="img/normal.png" alt="" width="100%" height="100%"/></p>
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