Hand–eye calibration using a target registration error model
Published in Healthcare Technology Letters/Augmented Environments for Computer Assisted Interventions (AE-CAI), 2017
Recommended citation: Chen ECS, Morgan I, Jayarathne U, Ma B, Peters TM, (2017). "Hand–eye calibration using a target registration error model"; in Healthcare Technology Letters, 4(5), pp. 157-162. https://ieeexplore.ieee.org/abstract/document/8107162
Surgical cameras are prevalent in modern operating theatres and are often used as a surrogate for direct vision. Visualisation techniques (e.g. image fusion) made possible by tracking the camera require accurate hand–eye calibration between the camera and the tracking system. The authors introduce the concept of ‘guided hand–eye calibration’, where calibration measurements are facilitated by a target registration error (TRE) model. They formulate hand–eye calibration as a registration problem between homologous point–line pairs. For each measurement, the position of a monochromatic ball-tip stylus (a point) and its projection onto the image (a line) is recorded, and the TRE of the resulting calibration is predicted using a TRE model. The TRE model is then used to guide the placement of the calibration tool, so that the subsequent measurement minimises the predicted TRE. Assessing TRE after each measurement produces accurate calibration using a minimal number of measurements. As a proof of principle, they evaluated guided calibration using a webcam and an endoscopic camera. Their endoscopic camera results suggest that millimetre TRE is achievable when at least 15 measurements are acquired with the tracker sensor ∼80 cm away on the laparoscope handle for a target ∼20 cm away from the camera.