collaborators

12 papers

eess.IV2026

Beyond Visibility: Real-Time Surface Accessibility Fields from Sparse LiDAR

Bradley Scott, Sam Schofield, Richard Green

Understanding which surfaces in a scene are physically accessible to a given tool is fundamental for robotic interaction, yet 3D perception systems typically stop at geometric reco…

cs.CV2026

Low-Cost Stereo Vision for Robust 3D Positioning of Thin Radiata Pine Branches in Autonomous Drone Pruning

Yida Lin, Bing Xue, Mengjie Zhang +2

Manual pruning of radiata pine, a species of major economic importance to New Zealand forestry, is hazardous, labour-intensive, and increasingly constrained by workforce shortages.…

cs.CV2026

Positioning radiata pine branches requiring pruning by drone stereo vision

Yida Lin, Bing Xue, Mengjie Zhang +2

This paper presents a stereo-vision-based system mounted on a drone for detecting and localising radiata pine branches to support autonomous pruning. The proposed pipeline comprise…

cs.CV2026

Real-Time Branch-to-Tool Distance Estimation for Autonomous UAV Pruning: Benchmarking Five DEFOM-Stereo Variants from Simulation to Jetson Deployment

Yida Lin, Bing Xue, Mengjie Zhang +2

Autonomous tree pruning with unmanned aerial vehicles (UAVs) is a safety-critical real-world task: the onboard perception system must estimate the metric distance from a cutting to…

cs.CV2026

UE5-Forest: A Photorealistic Synthetic Stereo Dataset for UAV Forestry Depth Estimation

Yida Lin, Bing Xue, Mengjie Zhang +2

Dense ground-truth disparity maps are practically unobtainable in forestry environments, where thin overlapping branches and complex canopy geometry defeat conventional depth senso…

eess.IV2026

Progressive Per-Branch Depth Optimization for DEFOM-Stereo and SAM3 Joint Analysis in UAV Forestry Applications

Yida Lin, Bing Xue, Mengjie Zhang +2

Accurate per-branch 3D reconstruction is a prerequisite for autonomous UAV-based tree pruning; however, dense disparity maps from modern stereo matchers often remain too noisy for…