3D tree reconstruction from laser range data

We present a method for reconstructing 3D models of tree branch structure from laser range data. Our approach is probabilistic, and uses general knowledge of tree structure to guide an iterative reconstruction process. Our goal is to recover parameters such as branch locations, angles, radii, and lengths, as well as connectivity information between branches. These parameters can then be fed into functional-structural plant models to study the relationships between the structure of a plant, its environment, and its internal biology. In this paper we present an algorithm for finding these parameters, and results on both simulated and real datasets.

Authors

• Jonathan Binney
• Gaurav S. Sukhatme

Keywords

• Laser modes
• Image reconstruction
• Biological system modeling
• Tree data structures
• Tree graphs
• Biosensors
• Clouds
• Robot sensing systems
• Plants (biology)
• Computer architecture
• Laser Ranging
• Laser Ranging Data
• Branch Lengths
• Simulated Datasets
• Tree Structure
• Reconstruction Process
• Plant Structure
• Branching Structure
• Branch Angle
• Simulated Data
• Partial Model
• Sensor Data
• Point Cloud
• Multi-core
• Tree Model
• Start Position
• Intuitive Way
• Sensor Model
• Side Branches
• Ray Tracing
• Trees In This Study
• End Of Branch
• Complicated Shapes
• Tree Parameters
• Laser Scanning Data