Paper
19 March 2018 Towards webcam-based tracking for interventional navigation
Mark Asselin, Andras Lasso, Tamas Ungi, Gabor Fichtinger
Author Affiliations +
Abstract
PURPOSE: Optical tracking is a commonly used tool in computer assisted surgery and surgical training; however, many current generation commercially available tracking systems are prohibitively large and expensive for certain applications. We developed an open source optical tracking system using the Intel RealSense SR300 webcam with integrated depth sensor. In this paper, we assess the accuracy of this tracking system. METHODS: The PLUS toolkit was extended to incorporate the ArUco marker detection and tracking library. The depth data obtained from the infrared sensor of the Intel RealSense SR300 was used to improve accuracy. We assessed the accuracy of the system by comparing this tracker to a high accuracy commercial optical tracker. RESULTS: The ArUco based optical tracking algorithm had median errors of 20.0mm and 4.1 degrees in a 200x200x200mm tracking volume. Our algorithm processing the depth data had a positional error of 17.3mm, and an orientation error of 7.1 degrees in the same tracking volume. In the direction perpendicular to the sensor, the optical only tracking had positional errors between 11% and 15%, compared to errors in depth of 1% or less. In tracking one marker relative to another, a fused transform from optical and depth data produced the best result of 1.39% error. CONCLUSION: The webcam based system does not yet have satisfactory accuracy for use in computer assisted surgery or surgical training.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark Asselin, Andras Lasso, Tamas Ungi, and Gabor Fichtinger "Towards webcam-based tracking for interventional navigation", Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 1057627 (19 March 2018); https://doi.org/10.1117/12.2293904
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Optical tracking

Cameras

Sensors

Infrared sensors

Infrared radiation

RGB color model

Computing systems

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