Color/Render a 3D Pointcloud in Python
<h1>Point Clouds and Spherical Images</h1>
<h2>Introduction</h2>
<p>By harnessing the duality between 3D point clouds and 2D spherical colored images, we can synergize robust 3D reconstruction algorithms with powerful 2D object detection techniques.</p>
<p>To simultaneously capture spherical colored images and point clouds, specialized devices such as depth sensors or LiDAR scanners are commonly equipped with spherical cameras.</p>
<p>Let’s establish a precise definition of the objects we’re talking about:</p>
<p><strong>3D point cloud</strong></p>
<ul>
<li>it provides a direct representation of the spatial layout of the scene</li>
<li>each point is defined by its 3D spatial coordinates (x, y, z)</li>
<li>additional attributes such as color, intensity, or other properties can be associated with each point</li>
</ul>
<p> </p>
<p>Colored point cloud of a room —Image by the author</p>
<p><strong>2D spherical image</strong></p>
<ul>
<li>It provides a panoramic view of the scene, capturing a wide field of view in all directions around a central viewpoint. For instance, it could be provided by two back-to-back fisheye cameras (See my previous Medium article Understanding 360 images )</li>
<li>Each pixel is defined by its 2D coordinates (latitude φ, longitude θ) and refers to a specific viewing direction, like on the earth’s surface.</li>
</ul>
<p><a href="https://betterprogramming.pub/color-render-a-3d-pointcloud-in-python-f67831442abd">Read More</a> </p>