3D Point Cloud Processing with PCL

"What's better than 2D?"

Three dimensional (3D) point cloud can be understood as a set of points in the Euclidean coordinate system, with every point has X-, Y-, and Z-coordinates. Combined with the corresponding normal vectors or normals, this set forms oriented points - providing 6 degrees of freedom (DOF). This article aims to briefly introduce readers to the 3D point cloud processing with an open source library called Point Cloud Library (PCL). Two examples of using PCL are given and visualized.

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A 3D point cloud can be acquired using range sensors such as Microsoft Kinect, ASUS Xtion, or laser scanners. These devices apply either triangulation or time-of-flight (TOF). Apart from that, using the autofocus system on conventional industrial cameras can also deliver 3D point clouds.

To process and visualize 3D point clouds, PCL offers various modules, e.g., filtering, segmentation, I/O, data structures, and visualization. The author has been tasked to implement several of these features in the open source application for image processing called MILAN. The implementations are available within one particular plug-in of MILAN. The following images are examples of using MILAN with PCL.

Figure 1 - The features of PCL in MILAN are accessible via a toolbox docked to the right side as seen above. This is also where the Kinect sensor can be used and controlled.

Figure 2: PCL Downsampling Filter, to reduce the size of an input cloud (left - 63792 vertices) to an output (right - 20462 vertices).

Figure 3: PCL Euclidean Cluster Segmentation, to segmentize spatially isolated point clouds.

Before using MILAN, the author has used the PCL tutorials and implemented them in separate Microsoft Visual Studio (MSVS) 2008 projects. The Service Packet 1 (SP 1) of this IDE needs to be installed, otherwise the developers can only code in Release mode.

Another alternative to MSVS is the Qt Creator. The author has covered this in one post on the app FingKinector 2.0. It was developed with Qt 4 along OpenCV 2.4.5. Without writing any .PRO file for the Qt project, the author used a CMakeLists.txt entirely to build this Qt project.