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Indoor localisation is a currently a key issue, from robotics to the Internet of Things. With hardware advancements making Ultra-Wideband devices more accurate and low powered (potentially even passive), this unlocks the potential of having such devices in common place around factories and homes, enabling an alternative method of navigation. Therefore, anchor calibration indoors becomes a key prob
In this paper, we consider a mobile platform with two cameras directed towards the floor. In earlier work, this specific problem geometry has been considered under the assumption that the cameras have been mounted at the same height. This paper extends the previous work by removing the height constraint, as it is hard to realize in real-life applications. We develop a method based on an equivalent
Many computer vision applications require robust estimation of the underlying geometry, in terms of camera motion and 3D structure of the scene. These robust methods often rely on running minimal solvers in a RANSAC framework. In this paper we show how we can make polynomial solvers based on the action matrix method faster, by careful selection of the monomial bases. These monomial bases have trad
To estimate the 6-DoF extrinsic pose of a pinhole camera with partially unknown intrinsic parameters is a critical sub-problem in structure-from-motion and camera localization. In most of existing camera pose estimation solvers, the principal point is assumed to be in the image center. Unfortunately, this assumption is not always true, especially for asymmetrically cropped images. In this paper, w
This paper introduces the first minimal solvers that jointly solve for affine-rectification and radial lens distortion from coplanar repeated patterns. Even with imagery from moderately distorted lenses, plane rectification using the pinhole camera model is inaccurate or invalid. The proposed solvers incorporate lens distortion into the camera model and extend accurate rectification to wide-angle
The problem of graph matching under node and pairwise constraints is fundamental in areas as diverse as combinatorial optimization, machine learning or computer vision, where representing both the relations between nodes and their neighborhood structure is essential. We present an end-to-end model that makes it possible to learn all parameters of the graph matching process, including the unary and
We introduce new, fine-grained action and emotion recognition tasks defined on non-staged videos, recorded during robot-assisted therapy sessions of children with autism. The tasks present several challenges: a large dataset with long videos, a large number of highly variable actions, children that are only partially visible, have different ages and may show unpredictable behaviour, as well as non
We propose drl-RPN, a deep reinforcement learning-based visual recognition model consisting of a sequential region proposal network (RPN) and an object detector. In contrast to typical RPNs, where candidate object regions (RoIs) are selected greedily via class-agnostic NMS, drl-RPN optimizes an objective closer to the final detection task. This is achieved by replacing the greedy RoI selection pro
In this paper we explore the role of duality principles within the problem of rotation averaging, a fundamental task in a wide range of computer vision applications. In its conventional form, rotation averaging is stated as a minimization over multiple rotation constraints. As these constraints are non-convex, this problem is generally considered challenging to solve globally. We show how to circu
Accurate histological classification and identification of fusion genes represent two cornerstones of clinical diagnostics in non-small cell lung cancer (NSCLC). Here, we present a NanoString gene expression platform and a novel platform-independent, single sample predictor (SSP) of NSCLC histology for combined, simultaneous, histological classification and fusion gene detection in minimal formali
Purpose: Paroxysmal atrial fibrillation is often suspected as a probable cause of cryptogenic stroke. Continuous long-term ECG monitoring using insertable cardiac monitors is a clinically effective technique to screen for atrial fibrillation and superior to conventional follow-up in cryptogenic stroke. However, more studies are needed to id
The main idea of this paper is to use distances between camera positions to recover the trajectory of a mobile robot. We consider a mobile platform equipped with a single fixed camera using images of the floor and their associated inter-image homographies to find these distances. We show that under the assumptions that the camera is rigidly mounted with a constant tilt and travelling at a constant
Popular Abstract in Swedish Vård och behandling av akut postoperativ och cancer-relaterad smärta: Patienters erfarenheter och uppfattningar i förhållande till hälsorelaterad livskvalitet och smärtans dimensioner Trots att det finns effektiva behandlingsmetoder för patienter med postoperativ smärta och cancer-relaterad smärta så lider många patienter av smärta. Denna avhandling beskriver patienterThis thesis describes patients in acute postoperative pain as well as patients with acute cancer-related pain in palliative care, and their experiences and perceptions of pain management in relation to HRQOL and the multidimensionality of pain. A combination of qualitative and quantitative methods was chosen. Data were collected using interviews and questionnaires; APS, SF:36 and a new developed q
Low-rank matrix factorization is an essential problem in many areas including computer vision, with applications in e.g. affine structure-from-motion, photometric stereo, and non-rigid structure from motion. However, very little attention has been drawn to minimal cases for this problem or to using the minimal configuration of observations to find the solution. Minimal problems are useful when eit
We propose new feature-based methods for rigid and affine image registration. These are compared to state-of-the-art intensity-based techniques as well as existing feature-based methods. On challenging datasets of brain MR and whole-body CT images, a significant improvement in terms of speed, robustness to outlier structures and dependence on initialization is shown.
In editors for visual languages it is often useful to provide interactive feedback that depends on the static semantics of the edited program. In this paper we demonstrate how such feedback can be implemented using reference attribute grammars. Because the implementation is declarative, it is easy to modularize compiler and editor computations, reusing the compiler's program model in the editor. F
Although digital inbound marketing has been widely researched within B2C industries, very little academic research has been done on the subject within B2B sectors. With today’s rapid flow of information and constant change in buying behavior when purchasing consumer goods, B2B buyers are also demanding a simpler, more digitized approach of gathering information. This master thesis focuses on ident
Non-human animals are often excluded from contemporary political theories, much to their detriment in terms of welfare and protection. The ‘political turn’ is a subset of animal ethicists concerned with moving beyond motivating moral status and instead discussing the politics of a shared human-animal society. This thesis evaluates Philip Pettit’s neo-republicanism as a theoretical framework for a
This study examines the long-term abnormal returns of stocks following Initial Public Offerings (IPOs) and Seasoned Equity Offerings (SEOs) on the Swedish and American markets from January 2000 to March 2021. Additionally, it examines the differences between Swedish and American companies and investigates factors influencing these disparities, focusing on the importance of market capitalization at
