One particular type of data that I find I increasingly deal with is 3D point cloud data. Point cloud data is fairly simple to grasp, it’s merely a “cloud” of points which each have their own individual coordinates in a Cartesian (think X, Y, Z) system. If that still doesn’t clear it up, watch this excellent video which shows off a cool example of point cloud data to model a shipping gallery. The sources of such point cloud datasets vary, including laser scanners, range cameras, or even your standard close-range photogrammetric techniques. In this post, I’m going to examine some typical techniques for fitting linear geometric shapes (lines, planes) to 3D point cloud data. It may get hairy with all the math involved, but I’ll try to keep the equations down where possible.
If you’ve ever owned a computer, you can probably imagine a few scenarios where having proper backups is helpful and to some extent, necessary. However, in many cases setting up an appropriate system for backing up your files can be either tedious or brings some air of uncertainty. Recently, I set up my own system for performing backups in (Debian) Linux, and I figured I’d write down my process for my own sake, but likewise to share with others who may not be so sure why or what they may want to backup.
A short while back, a friend made mention of how he noticed that Android places a hard limit on the audio bitrate in videos recorded from the device. I found it interesting that Android by default reduces the audio quality to a hard limit, so I thought I’d post about the issue and explore it a little further. By the end of this article, I hope to have explained some basic signal terminology, as well as have shown you how to improve the quality of audio recorded from android devices.