Depth Estimation for Oral Cavity by Shape from Shading with Endoscope

Tracheal intubation for patients with respiratory infectious diseases requires doctors to wear a full set of protective clothing, which takes a certain time. How to protect doctors from infection when facing an emergency operation has become an important issue. The intubation robot may solve this contradiction. To provide visual information for real-time path planning for robotic intubation, this study recovers depth information about the oral environment using the low-cost and widely used endoscopic. Since the oral cavity is small and has less texture, the Shape from Shading (SFS) method may be a good choice for oral depth estimation. This paper proposes the “oral elbow” hypothesis, filters outliers caused by saliva, calculates the 3-D contour map, and highlights the contour map features from different views. Oral images are obtained from a healthy person and a silicon dummy. This work expands the application scenarios of depth estimation to the oral environment; provides depth information for the visual navigation of the intubation surgical robot.