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Version: 7.0

Supported Fiducials

A detector is a description of what feature(s) to identify in an observation to generate our object space.

Markerboard​

Target: Markerboard

Markerboards are similar to checkerboards, but contain a series of coded markers in the empty spaces of the checkerboard. These codes are most often in the form of April or ArUco tags, which allow for better identification and isolation of features.

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A Markerboard is the preferred Detector type for camera data in MetriCal.

Circular Markerboard​

Target: Circular Markerboard

This circular markerboard is similar to a markerboard in almost every way, but cut into a circle. The target also uses a retroreflective border around the circle. This target type is required to perform a Camera ↔ LiDAR or LiDAR ↔ LiDAR calibration.

If you're interested in procuring one of these boards, please contact our support.

Aprilgrid​

Target: Aprilgrid

Aprilgrids are patterned sets of Apriltags. They have constrasting squares in the corner of every tag; this provides feature detection algorithms more information to derive corner locations.

Markers​

Target: Markers

"Markers" is a general catch-all for a collection of signalized markers, e.g. a calibration space made up of many unconnected ArUco or April tags.

Checkerboard​

Target: Checkerboard

Anyone who has ever tried their hand at calibration is familiar with the checkerboard. This is a flat, contrasting pattern of squares with known dimensionality. It's known for its ease of creation and flexibility in use.

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While MetriCal supports checkerboards, it is important to note some limitations:

  • Points on the checkerboard are ambiguous. No calibration system can reliably tell the difference between a checkerboard rotated 180° and one that is not rotated at all. The same applies between rotations of 90° and 270°. This ambiguity means that MetriCal cannot reliably differentiate extrinsics, which causes projective compensations.
  • The entire checkerboard needs to be visible in the field-of-view of the camera. With coded targets or asymmetric patterns, MetriCal can still identify key features without the full target in view.

We recommend using coded detectors like the Markerboard whenever possible. This allows MetriCal to be more flexible to different data collection practices, and reduces the burden on you to keep the entire object space in frame at all times.