π€ AI Summary
Extracting slender geometric structures from Gaussian splatting scenes for physical simulation is highly challenging due to the absence of explicit topological connectivity and significant noise inherent in Gaussian primitives. This work proposes a user-sketch-guided, screen-space shortest path approach that leverages dynamic programming to efficiently construct polyline meshes, enabling robust reconstruction of slender object geometries. To the best of our knowledge, this is the first method to achieve interactive extraction of coherent slender structures directly from Gaussian splatting representations, effectively overcoming the difficulties posed by missing topology and noisy input. Extensive experiments across multiple real-world scenes demonstrate the robustness and practical utility of the proposed technique.
π Abstract
Physics simulation of slender elastic objects often requires discretization as a polyline. However, constructing a polyline from Gaussian splatting is challenging as Gaussian splatting lacks connectivity information and the configuration of Gaussian primitives contains much noise. This paper presents a method to extract a polyline representation of the slender part of the objects in a Gaussian splatting scene from the userβs sketching input. Our method robustly constructs a polyline mesh that represents the slender parts using the screen-space shortest path analysis that can be efficiently solved using dynamic programming. We demonstrate the effectiveness of our approach in several in-the-wild examples.