Multiple Kinect V2 Calibration

Abstract

In this paper, we propose a method to easily calibrate multiple Kinect V2 sensors. It requires the cameras to simultaneously observe a 1D object shown at different orientations (three at least) or a 2D object for at least one acquisition. This is possible due to the built-in coordinate mapping capabilities of the Kinect. Our method follows five steps: image acquisition, pre-calibration, point cloud matching, intrinsic parameters initialization, and final calibration. We modeled radial and distortion parameters of all the cameras, obtaining a root mean square reprojection error of 0.2 pixels on the depth cameras and 0.4 pixels on the color cameras. To validate the calibration results we performed point cloud fusion with color and 3D reconstruction using the depth and color information from four Kinect sensors.Key words: Camera calibration, Kinect V2 system, Multiple cameras Umjeravanje Kinect V2 sustava s više kamera. U ovom je radu predložena metoda za jednostavno umjeravanje proizvoljnog broja senzora Kinect V2. Izvodi se istovremenim snimanjem objekta s više kamera. Jednodimenzionalan objekt potrebno je snimiti s najmanje 3 različite orijentacije, a dvodimenzionalan s najmanje jedne orijentacije. Istovremeno snimanje s više kamera moguće je zahvaljujući integriranom mapiranju koordinata u Kinect sustavu. Predložena metoda izvodi se u pet koraka: akvizicija slike, predumjeravanje, uskladivanje oblaka točaka, inicijalizacija intrinzičnih parametara i konačno umjeravanje. U radu su modelirani radijalni i distorzijski parametri svih kamera, pričemu se ostvaruje korijen srednje kvadratične pogreške ponovne projekcije iznosa 0:2 piksela na kamerama dubine i 0:4 piksela na kamerama u boji. Za validaciju rezultata umjeravanja provedena je fuzija oblaka točaka s rekonstrukcijom trodimenzionalnog objekta i boje korištenjem informacije o dubini i boji š cetiri Kinect senzora.

A Comparison of Dual-Kinect and Vicon Tracking of Human Motion for Use in Robotic Motion Programming

“…To ensure no joint occlusion, the test subject is required to stand with straight legs and both arms fully extended, pointing sideways in a T-Pose for less than two seconds, during which 50 frames are acquired by both Kinect sensors. Then, the joint position estimates are averaged and fed into the calibration algorithm, which is based on an approach similar to the multiple Kinect Calibration described by Córdova-Esparza et al [15]. The coordinate transformation is calculated via Corresponding Point Set Registration [16].…”

Calibration of a panoramic 3D reconstruction system

“…The augmented view is useful in many applications such as three‐dimensional (3D) reconstruction [1–7], video surveillance [8], robot navigation [9], and quality control [10] among others. These applications usually require the extraction of metric information from the environment, which can only be achieved with a calibrated system.…”

Dynamic Measurement of Portos Tomato Seedling Growth Using the Kinect 2.0 Sensor

“…The use of the depth sensor in an outdoor environment required its calibration [93,94]. Therefore, we performed the sensor calibration in an indoor environment controlling the illumination received by the pattern, mainly in the back of the pattern and the front of the Kinect sensor.…”