VI-Rig: 4 IMUs + 4 cameras

Demo and values

One MVIS camera + IMU run on recording 4imus_4cams_01: all four cameras and all four IMUs solved together.

The scene MVIS recovered from this dataset, as on the homepage. The values beside it come from this page's run.

Reprojection median0.25 px

cam0–cam1 baseline63.7 mm

cam0 td−5.41 ms

cam0 lever arm130.8 mm

Reprojection is how far, in pixels, the detected corners lie from where the solve puts them. td is the camera–IMU time offset, and the lever arm is the camera–IMU position offset.

Calibration process

MVIS's own player, from this run: the detected board corners, then the rig's path as the solve refines it. Press Play or drag the bar; pick a camera card to look through that camera. We publish no camera images.

Solved rig

The solved positions and orientations, to scale in the IMU frame. Drag sideways to orbit. Tap a sensor to see its values.

3DFrontTopSide+−

Sensor	fx, fy, cx, cy px	Lever mm	log(R) rad	td ms	Readout ms	t_ga ms	Reprojection px
cam0	286.5, 286.3, 414.9, 402.6	[+64.3, −110.6, −27.1]	[−0.0318, −2.2176, +2.2151]	−5.41	global		0.253
cam1	286.5, 286.1, 414.4, 397.0	[+0.7, −108.9, −27.1]	[−0.0392, −2.2123, +2.2155]	−7.47	global		0.245
cam2	426.9, 426.4, 350.4, 265.9	[−89.0, −112.4, −22.3]	[−0.0039, −2.0835, +2.2769]	−123.25	16.68		0.229
cam3	423.6, 423.1, 336.5, 256.9	[−148.3, −110.2, −20.9]	[+0.0135, −2.1129, +2.2597]	−123.30	16.73		0.243
IMU (base)		0	0	0		−0.82 ± 0.02
IMU gx3_25		[−122.8, −45.3, −3.1]	[+2.2502, +2.1849, −0.0279]	−0.69		+0.10 ± 0.02
IMU gx3_35		[−82.3, −46.2, −3.5]	[+2.2304, +2.2070, −0.0192]	−2.07		+0.01 ± 0.02
IMU t265		[+54.7, −107.4, −30.3]	[+1.5724, −0.0054, −0.0113]	−7.17		−6.74 ± 0.02

Lever arms and rotations are each sensor in the base IMU frame; rotation is log(R) in rad. td is the time offset to the base IMU, t_imu = t_sensor + td. Reprojection is the median per camera (all cameras: median 0.246 px): how well the model fits the corners, not how accurate it is.

Check against a reference

No published reference. No published calibration exists for this rig, so this page has nothing to compare against. What we can show is how much each value moves from one recording to the next. All 15 recordings and tools: Dataset eval →

Config and run

virig_4imus_4cams_cam_imu.yaml

input:
  format: ros1
  path: 4imus_4cams_01.bag
  cam_topics:
  - /t265/fisheye1/image_raw
  - /t265/fisheye2/image_raw
  - /elp/split_sync_image_node/left/image_raw
  - /elp/split_sync_image_node/right/image_raw
  imu_topics:
  - /imu/data
  - /gx3_25/data
  - /gx3_35/imu/data
  - /t265/imu
  window_mode: motion
  segment_length: 80.0
board:
  board_type: apriltag
  rows: 6
  cols: 6
  tag_size: 0.088
  tag_spacing: 0.3
  tag_family: t36h11
  heights_file: board_shape_4imus_4cams.yaml
camera_input:
  path: camera_prior.yaml
  cameras:
  - {}
  - factor_hz: 4.0
  - estimate_readout: true
    factor_hz: 4.0
  - estimate_readout: true
    factor_hz: 4.0
solve:
  max_iterations: 40
  corner_subsample: two_anti
  estimate_t_ga: true
  sigma_t_ga: 0.01
  vision_pose: imu
  sigma_g: 0.00065
  sigma_a: 0.0026
  sigma_bg: 0.001
  sigma_ba: 0.002
estimate:
  board_points: true
  camera:
    intrinsics: true
    tr: false
    td: true
    extrinsics: true
  imu:
    intrinsics: dw_da
    model: calyx
    extrinsics: true
    td: true
output:
  path: cam_imu.json

shell

mvis cam-imu -c virig_4imus_4cams_cam_imu.yaml

The marked lines are the choices that matter for this rig:

• input.imu_topics: Four IMU topics. The first is the base IMU; the other three are solved against it.
• input.window_mode: MVIS picks the 80 s window with the most motion.
• camera_input.cameras: The ELP cameras are rolling shutter, so their readout time is estimated. The three cameras after the first are added to the graph at 4 Hz, which keeps the solve small.
• solve.sigma_g: The same IMU noise values as the 3-camera example, which has the same Xsens base IMU.
• estimate.board_points: The printed board is not quite flat, so its shape is estimated too.
• estimate.camera.intrinsics: Camera intrinsics stay free in the camera + IMU solve.

This is the config of the run on this page, with every path cut to its file name. Point the paths at your copy.

The solve took about 12 min on one desktop. It writes cam_imu.json, a calibration YAML and a report beside the config.

MVIS

MVIS main, 2026-11-10

Run date

2026-11-10

Data

VI-Rig 4 IMUs + 4 cams dataset page →

Config

virig_4imus_4cams_cam_imu.yaml, above

Command

mvis cam-imu -c virig_4imus_4cams_cam_imu.yaml

Dataset

• Recording 4imus_4cams_01, one of the 15 recordings of this rig. MVIS picks the 80 s window with the most motion.
• Cameras: the two T265 fisheye cameras (global shutter) and the ELP stereo pair (rolling shutter), all with the equidistant lens model.
• IMUs: the Xsens MTi is the base IMU; the two MicroStrain units and the T265's own IMU are solved against it.
• Board: AprilGrid 6×6, tag 88 mm, spacing 0.3, t36h11.
• Solve window: 80.0 s.

Download: VI-Rig 4 IMUs + 4 cams dataset page → The recordings are listed there, not copied here.

AprilGrid 6 × 6, 660 × 660 mm. Standard pattern, to scale