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 (230, 240, 295), position and orientation relative to the other cameras among the plurality of cameras (230, 240, 295); the plurality of cameras (230A,..., 230C; 295A,..., 295H) sharing an overlapped part in their respective fields of view (260, 290) in which a known test object (275, 500) is located, such that the known test object (275, 500) is viewed by at least two cameras (230, 295); identifying calibration parameters for the plurality of cameras, the calibration parameters including a rotation matrix and a translation matrix for each camera (230, 295); receiving a plurality of images of the known test object (275, 500) captured by the plurality of cameras, the known test object (275, 500) 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 (275, 500); creating a 3D model of the known test object (275, 500) 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 (275, 500), the calibration measures including: location, size, texture, shape, color, and information about features on the test object (275, 500) 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 (230, 240, 295) 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 (230, 240, 295), position and orientation relative to the other cameras among the plurality of cameras (230, 240, 295); the plurality of cameras (230A,..., 230C; 295A,..., 295H) sharing an overlapped part in their respective fields of view (260, 290) in which a known test object (275, 500) is located, such that the known test object (275, 500) is viewed by at least two cameras (230, 295); identifying calibration parameters for the plurality of cameras, the calibration parameters including a rotation matrix and a translation matrix for each camera (230, 295); receiving a plurality of images of the known test object (275, 500) captured by the plurality of cameras, the known test object (275, 500) 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 (275, 500); creating a 3D model of the known test object (275, 500) 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 (275, 500), the calibration measures including: location, size, texture, shape, color, and information about features on the test object (275, 500) 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 (230, 240, 295) to reduce the calibration error; and performing additional iterations of calibration until the calibration error is below a calibration error threshold.