RESUMO
The glasses-free three dimensional(3D) endoscopic display system provides the surgeon with the depth information of the minimally invasive surgery scene obtained from the binocular perspective, which can effectively relieve the surgeon's posture fatigue and visual fatigue during the long-term surgery, and assist in the operation of surgical instruments more accurately to reduce the damage to the surrounding tissues of the operation area. However, the glasses-free 3D display device currently has the problem of a narrow optimal viewing zone and easy crosstalk, especially in the surgical teaching application scenario, which performs poorly. In order to overcome the limitation of the narrower field of view, we introduce deep learning algorithms to detect and locate multiple faces, fine-tune the 3D display grating of the endoscope, rearrange pixels, and change the best view area, so that more people can get the best view. The experimental results show that the face detection accuracy of the method is 97.88%, and the detection time is 135 frames/ms, which achieves high accuracy while maintaining real-time performance.