LAUSR

BACKGROUND: The human body model in the virtual surgery system is generally nested by multiple complex models and each model has quite complex tangent and curvature change. In actual rendering, if all details of the human body model are rendered with high performance, it may cause the stutter due to insufficient hardware performance. If the human body model is roughly rendered, the details of the model cannot be well represented. OBJECTIVE: In order to realize the real-time rendering of complex models in virtual surgical systems, this paper proposes an improved adaptive tessellation rendering algorithm, which includes offline and online parts. METHODS: The offline part mainly completes data reading and data structure constructing. The online part performs the surface subdivision operation in-real time for each frame, which includes the subdivision operation of the control points and surface evaluation. The offline part simplifies the subdivision step by recording the surface subdivision hierarchy using a quadtree and using control templates to record control point information. RESULTS: The online part reduces computation time by using a matrix to record topological relationships between vertices and vertex weights. The online part can compress the time complexity of traversing the quadtree of different subdivision levels to O⁢(n⁢log⁡n) by establishing an association with the quadtree of each subdivision level and using the greedy algorithm to complete the traversal of the quadtree. Finally, the adaptive tessellation rendering algorithm proposed in this paper is compared with other commonly used tessellation algorithms. CONCLUSION: The algorithm has advantages in computational efficiency and graphical display.