Detecting aligned 3D keypoints is essential under many scenarios such as object tracking,
shape retrieval and robotics. However, it is generally hard to prepare a high-quality dataset …

The ability of mobile robots to sense, interpret and map their environments in human terms is
decisive for their applicability to everyday activities hereafter. Bearing this view in mind, we …

A novel method is proposed for the absolute pose estimation of a central 2D camera with
respect to 3D depth data without the use of any dedicated calibration pattern or explicit point …

Vehicle localisation is an important and challenging task in achieving autonomous driving.
This work presents a box particle filter framework for vehicle self-localisation in the presence …

Point-cloud processing for extracting geometric features is difficult due to the highly non-
linear rotation variance and measurement noise corrupting the data. To address these …

With the increasing popularity of Building Information modelling (BIM), the demand for
accurate as-built models of existing buildings is rising. However, the manual creation of …

Image semantic segmentation is a challenging problem for low‐level computer vision.
Recently, deep convolutional neural networks (DCNNs) have been proved to achieve …

Detecting 3D keypoints with semantic consistency is widely used in many scenarios such as
pose estimation, shape registration and robotics. Currently, most unsupervised 3D keypoint …

In this work we propose a novel next best view (NBV) generation algorithm for volumetric
information maximization. The primary data source is a Time-of-Flight (ToF) camera and the …

The key component of the precision agriculture application is the integration of autonomous
robots in outdoor fields. Autonomous locomotion is based on estimating the traversability …