3 accepted papers
Robots operating in low-light conditions with conventional cameras face significant challenges due to the low signal-to-noise ratio in the images. Previous work has demonstrated the use of burst-imaging techniques to partially overcome this issue. This study proposes a novel feature finder that enha
Images captured under extremely low light conditions are noise-limited, which can cause existing robotic vision algorithms to fail. In this letter we develop an image processing technique for aiding 3D reconstruction from images acquired in low light conditions. Our technique, based on burst photogr
This paper presents an autonomous approach to tree detection and segmentation from high resolution airborne LiDAR pointclouds, such as those collected from a UAV, that utilises region-based CNN and 3D-CNN deep learning algorithms. Trees are first detected in 2D before individual trees are further ch…