Easy to Calibrate: Marker-Less Calibration of Multiview Azure Kinect

Reconstructing a three-dimensional (3D) environment is an indispensable technique to make augmented reality and virtuality feasible. A Kinect device efficient tool for reconstructing 3D environments, using multiple devices enables the enhancement of reconstruction density expansion virtual spaces. To employ simultaneously, need be calibrated with respect each other. There are several schemes available that calibrate images generated from devices, including marker detection method. In this study, we introduce markerless calibration Azure avoids drawbacks detection, which directly affects accuracy; it offers superior user-friendliness, efficiency, accuracy. Further, applied joint tracking algorithm approximate calibration. Traditional methods require information joints calibration; however, Kinect, latest version requires only one joint. The obtained result was further refined iterative closest point algorithm. We conducted experimental tests confirmed enhanced efficiency accuracy proposed method when compared conventional marker-based