Alternative online extrinsic calibration techniques for minimally invasive surgery

ABSTRACT

One of the main challenges in external optical tracking device based augmented reality (AR) is the extrinsic calibration. Such an example is calibration of the endoscope camera with the tracking device to estimate the transformation between the endoscope-mounted marker and endoscope sensor. In this paper, we describe two alternative techniques to the Hand-Eye method for online calibration. First, we describe a direct technique based on estimating rigid transformation from corresponding point sets and our idea of improving the calibration efficiency by collecting corresponding points covering broader area of the endoscope and tracker field-of-view (FOV). Then, we describe a technique based on estimation of position and orientation of a planar object from camera image. The main advantage of these techniques is that they are easily repeatable in applications where a change in the relation between camera sensor and camera-mounted marker is possible during the run-time of the AR application.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.8 Scene Analysis
          Subjects: Tracking

Additional Classification:
  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.5 Computational Geometry and Object Modeling
          Subjects: Hierarchy and geometric transformations
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.9 Applications

Keywords:
extrinsic calibration, hand-eye, pose estimation