Smart-Tree: Neural Medial Axis Approximation of Point Clouds for 3D Tree Skeletonization

• URL: http://arxiv.org/abs/2303.11560v2
• Date: Fri, 5 May 2023 10:41:23 GMT
• Title: Smart-Tree: Neural Medial Axis Approximation of Point Clouds for 3D Tree Skeletonization
• Authors: Harry Dobbs, Oliver Batchelor, Richard Green, James Atlas
• Abstract summary: Smart-Tree is a supervised method for approximating the medial axes of branch skeletons from a tree point cloud. A greedy algorithm performs robust skeletonization using the estimated medial axis. We evaluate Smart-Tree using a multi-species synthetic tree dataset and perform qualitative analysis on a real-world tree point cloud.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper introduces Smart-Tree, a supervised method for approximating the medial axes of branch skeletons from a tree point cloud. Smart-Tree uses a sparse voxel convolutional neural network to extract the radius and direction towards the medial axis of each input point. A greedy algorithm performs robust skeletonization using the estimated medial axis. Our proposed method provides robustness to complex tree structures and improves fidelity when dealing with self-occlusions, complex geometry, touching branches, and varying point densities. We evaluate Smart-Tree using a multi-species synthetic tree dataset and perform qualitative analysis on a real-world tree point cloud. Our experimentation with synthetic and real-world datasets demonstrates the robustness of our approach over the current state-of-the-art method. The dataset and source code are publicly available.

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