In this paper, we present a simple yet effective calibration method for multiple Kinects, i.e. a method that finds the rel ative position of RGB-depth cameras, as opposed to conven tional methods that find the relative position of RGB cameras. We first find the mapping function between the RGB camera and the depth camera mounted on one Kinect. With such a mapping function, we propose a scheme that is able to esti mate the 3D coordinates of the extracted corners from a stan dard calibration chessboard. To this end, we are able to build the 3D correspondences between two Kinects directly. This simplifies the calibration to a simple Least-Square Minimiza tion problem with very stable solution. Furthermore, by using two mirrored chessboard images on a thin board, we are able to calibrate two Kinects facing each other, something that is intractable using traditional calibration methods. We demon strate our proposed method with real data and show very accu rate calibration results, namely less than 7mm reconstruction error for objects at a distance of I.Sm, using around 7 frames for calibration.