A method for calibrating a camera rig system , the method comprising: receiving configuration information about a plurality of cameras in the camera rig system , the configuration information including, for each camera among the plurality of cameras , position and orientation relative to the other cameras among the plurality of cameras ; the plurality of cameras (230A,..., 230C; 295A,..., 295H) sharing an overlapped part in their respective fields of view in which a known test object is located, such that the known test object is viewed by at least two cameras ; identifying calibration parameters for the plurality of cameras , the calibration parameters including a rotation matrix and a translation matrix for each camera ; receiving a plurality of images of the known test object captured by the plurality of cameras , the known test object having known calibration measures including: location, size, texture, shape, color, and information about features on the test object including visual features of visually distinguishable points on the known test object ; creating a 3D model of the known test object based on the identified calibration parameters and the received plurality of images ; calculating a calibration error that reflects differences between calibration measures of the created 3D model of the known test object , the calibration measures including: location, size, texture, shape, color, and information about features on the test object including visual features of visually distinguishable points, and the known calibration measures of the known test object ; modifying the calibration parameters for the plurality of cameras to reduce the calibration error ; and performing additional iterations of calibration until the calibration error is below a calibration error threshold. receiving configuration information about a plurality of cameras in the camera rig system , the configuration information including, for each camera among the plurality of cameras , position and orientation relative to the other cameras among the plurality of cameras ; the plurality of cameras (230A,..., 230C; 295A,..., 295H) sharing an overlapped part in their respective fields of view in which a known test object is located, such that the known test object is viewed by at least two cameras ; identifying calibration parameters for the plurality of cameras , the calibration parameters including a rotation matrix and a translation matrix for each camera ; receiving a plurality of images of the known test object captured by the plurality of cameras , the known test object having known calibration measures including: location, size, texture, shape, color, and information about features on the test object including visual features of visually distinguishable points on the known test object ; creating a 3D model of the known test object based on the identified calibration parameters and the received plurality of images ; calculating a calibration error that reflects differences between calibration measures of the created 3D model of the known test object , the calibration measures including: location, size, texture, shape, color, and information about features on the test object including visual features of visually distinguishable points, and the known calibration measures of the known test object ; modifying the calibration parameters for the plurality of cameras to reduce the calibration error ; and performing additional iterations of calibration until the calibration error is below a calibration error threshold. <EOS>