Convenient calibration method for unsynchronized camera networks using an inaccurate small reference object

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In this paper, a new and convenient calibration algorithm is proposed for unsynchronized camera networks with a large capture volume. The proposed method provides a simple and accurate means of calibration using a small 3D reference object. Moreover, since the inaccuracy of the object is also compensated simultaneously, the manufacturing cost can be decreased. The extrinsic and intrinsic parameters are recovered simultaneously by capturing an object placed arbitrarily in different locations in the capture volume. The proposed method first resolves the problem linearly by factorizing projection matrices into the camera and the object pose parameters. Due to the multi-view constraints imposed on factorization, consistency of the rigid transformations among cameras and objects can be imposed. These consistent estimation results can be further refined using a non-linear optimization process. The proposed algorithm is evaluated via simulated and real experiments in order to verify that it is more efficient than previous methods.