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At present, feature-based 3D reconstruction and tracking technology is widely applied in the medical field. In minimally invasive surgery, the surgeon can achieve three-dimensional reconstruction through the images obtained by the endoscope in the human body, restore the three-dimensional scene of the area to be operated on, and track the motion of the soft tissue surface. This enables doctors to have a clearer understanding of the location depth of the surgical area, greatly reducing the negative impact of 2D image defects and ensuring smooth operation. In this study, firstly, the 3D coordinates of each feature point are calculated by using the parameters of the parallel binocular endoscope and the spatial geometric constraints. At the same time, the discrete feature points are divided into multiple triangles using the Delaunay triangulation method. Then, the 3D coordinates of feature points and the division results of each triangle are combined to complete the 3D surface reconstruction. Combined with the feature matching method based on convolutional neural network, feature tracking is realized by calculating the three-dimensional coordinate changes of the same feature point in different frames. Finally, experiments are carried out on the endoscope image to complete the 3D surface reconstruction and feature tracking.

Currently, an acceleration sensor based on fiber Bragg grating (FBG) has been widely used. A cantilever FBG accelerometer is designed. The simulation of this structure was implemented by finite element software (ANSYS) to analyze its sensing performance parameters. And then the optimized structure was produced and calibration experiments were conducted. On the basis of simulation, optical fiber is embedded in the inner tank of the vibrating mass, and Bragg grating is suspended above the cantilever structure, which can effectively avoid the phenomenon of center wavelength chirp or broadening, and greatly improve the sensitivity of the sensor. The experimental results show that the FBG accelerometer exhibits a sensitivity of 75 pm∕ðm∕s 2 Þ (100 Hz) and dynamic range of 60 dB. Its linearity error is <2.31% and repeatability error is <2.76%. And the resonant frequency is ∼125 Hz. The simulation results match the experimental results to demonstrate the good performance of FBG accelerometer, which is expected to be used in the actual project.

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