Distortion correction of depth data from consumer depth cameras

Since the introduction of the Microsoft Kinect in November 2010, low cost consumer depth cameras have rapidly increased in popularity. Their integral technology provides a means of low cost 3D scanning, extending its accessibility to a far wider audience. Previous work has shown the 3D data from consumer depth cameras to exhibit fundamental measurement errors: likely due to their low cost and original intended application. A number of techniques to correct the errors are presented in the literature, but are typically device specific, or rely on specific open source drivers. Presented here is a simple method of calibrating consumer depth cameras, relying only on 3D scans of a plane filling the field of view: thereby compatible with any device capable of providing 3D point cloud data. Validation of the technique using a Microsoft Kinect sensor has shown non planarity errors to reduce to around ± 3mm: nearing the device’s resolution. Further validation based on circumference measures of a cylindrical object has shown a variable error of up to 45mm to reduce to a systematic overestimation of 10mm, based on a 113mm diameter cylinder. Further work is required to test the proposed method on objects of greater complexity and over greater distances. However, this initial work suggests great potential for a simple method of reducing the error apparent in the 3D data from consumer depth cameras: possibly increasing their suitability for a number of applications.