Recent methods for 3D reconstruction and rendering increasingly benefit from end-to-end
optimization of the entire image formation process. However, this approach is currently …

In this paper we introduce the Tangent Sampson error, which is a generalization of the
classical Sampson error in two-view geometry that allows for arbitrary central camera …

From a single image, visual cues can help deduce intrinsic and extrinsic camera parameters
like the focal length and the gravity direction. This single-image calibration can benefit …

Low-dimensional parametric models are the de-facto standard in computer vision for
intrinsic camera calibration. These models explicitly describe the mapping between …

Camera calibration is a crucial step in photogrammetry and 3D vision applications. In
practical scenarios with a long working distance to cover a wide area, target-based …

Wide-angle cameras are uniquely positioned for mobile robots, by virtue of the rich
information they provide in a small, light, and cost-effective form factor. An accurate …

Multi-model fitting aims to robustly estimate the parameters of various model instances in
data contaminated by noise and outliers. Most previous works employ only a single type of …

Accurate checkerboard detection is of vital importance for computer vision applications, and
a variety of checkerboard detectors have been developed in the past decades. While some …

Safe & smart move (SSM) aims to help industrial vehicular robot (IVR), such as warehousing
robots, running safely and smartly by detecting the obstacles in front and maintaining a safe …

Abstract n this dissertation we explore the usage of probabilistic machine learning
techniques for calibrating 3D measuring devices and applications. More specifically, we …