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Technical Brief

A Framework for Calibrating and Benchmarking Computer Vision Algorithms in Surgical Robotics1

[+] Author and Article Information
Rodney Dockter, Timothy M. Kowalewski

Department of Mechanical Engineering,
University of Minnesota,
Minneapolis, MN 55455

Accepted and presented at the Design of Medical Devices Conference (DMD2014), Minneapolis, MN, April 7–10, 2014.DOI: 10.1115/1.4027047

Manuscript received February 21, 2014; final manuscript received March 3, 2014; published online July 21, 2014. Editor: Arthur G. Erdman.

J. Med. Devices 8(3), 030926 (Jul 21, 2014) (2 pages) Paper No: MED-14-1077; doi: 10.1115/1.4027047 History: Received February 21, 2014; Revised March 03, 2014

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References

Pun, T., Geric, G., and Ratib, O., 1994, “Image Analysis and Computer Vision in Medicine,” Comput. Med. Imaging Graph., 18(2), pp. 85–96. [CrossRef] [PubMed]
Zhang, Z., 2000, “A Flexible New Technique for Camera Calibration,” IEEE Trans. Pattern Anal. Mach. Intell., 22(11), pp. 1330–1334. [CrossRef]
Tsai, R., 1987, “A Versatile Camera Calibration Technique for High-Accuracy 3D Machine Vision Metrology Using Off-the-Shelf TV Cameras and Lenses,” IEEE J. Rob. Autom., 3(4), pp. 323–344. [CrossRef]
Dockter, R., and Kowalewski, T., 2013, “A Low-Cost Computer Vision Based Approach for Tracking Surgical Robotic Tools,” ASME J. Med. Devices, 7(3), p. 030917. [CrossRef]

Figures

Grahic Jump Location
Fig. 2

Calibration routine using lathe

Grahic Jump Location
Fig. 3

Reference trajectory in lathe

Grahic Jump Location
Fig. 4

Depth versus disparity plot

Grahic Jump Location
Fig. 5

Calibration data for radial distortion

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