Motion capture of hand movements using stereo vision for minimally invasive vascular interventions

This source preferred by Wen Tang

Authors: Huang, D., Ding, Y. and Tang, W.

Start date: 12 August 2011

Publisher: IEEE

This data was imported from Scopus:

Authors: Huang, D., Tang, W., Ding, Y., Wan, T., Wu, X. and Chen, Y.

Journal: Proceedings - 6th International Conference on Image and Graphics, ICIG 2011

Pages: 737-742

ISBN: 9780769545417

DOI: 10.1109/ICIG.2011.125

A virtual reality (VR) based training system for Minimally Invasive Vascular Surgery can be a very useful training tool for improving skills and reducing errors in operation. Computer vision techniques have the potential to be incorporated into a VR based training system for developing low cost, high accuracy and flexible systems in this area. In this paper, we present an interactive 3D training system that uses stereo vision to capture hand movements as the input operations for the system. The standard operations i.e. pushing, pulling and twisting are captured with stereo vision based on the improved Camshift tracking algorithm and parallel alignment model theory to acquire hand gestures information. We present a new approach to calculate virtual pushing/pulling force and turning angle as extra inputs for understanding these essential operations. In addition, an algorithm that enables the simulator to model guidewire and catheter insertions realistically is presented through these basic actions. The experiment results demonstrate that stereo vision based training system is useful and effective for simulating guidewire insertion procedures with low system cost and flexible operations. © 2011 IEEE.

The data on this page was last updated at 04:57 on May 24, 2019.