Study on Reconstruction and Feature Tracking of Silicone Heart 3D Surface

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.

INFLUENCE OF ILLUMINATION CHANGES ON IMAGE-BASED 3D SURFACE RECONSTRUCTION

The paper investigates the influence of lighting conditions on image-based 3D surface reconstruction, with particular focus on periodic photogrammetric surveys for monitoring and 3D mapping applications. The analyses focus on the accuracy and completeness of each DSM and the daily and hourly repeatability of repeated photogrammetric surveys. Three test sites with rock slopes with a different orientation to the sun and different slope characteristics (slope, pattern, amount of outcropping elements that cast shadows) have been considered to ensure that results can give a general indication of the behaviours in different light conditions. In addition, a simulated virtual test site is included in the study to allow controlled image acquisition and evaluate the effect of the sun’s inclination on the DSM accuracy without influence of other weather conditions. The results show that, although there is an optimal time for the acquisitions, if particularly unfavourable light conditions are excluded, the accuracy reduction with time variation is always below 30%. The repeatability analyses by day and by time highlight a good consistence between DEMs belonging to the same day but acquired at different times and, also, between DEMs acquired at the same time but on different days. This suggests that reliable results can be obtained during continuous monitoring of, for instance, rock faces to identify rockfalls.