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In this paper we present a new method for creating polynomialsolvers for problems where a (possibly infinite) subsetof the solutions are undesirable or uninteresting. Thesesolutions typically arise from simplifications made duringmodeling, but can also come from degeneracies which areinherent to the geometry of the original problem.The proposed approach extends the standard action matrixmethod to
There is a significant interest in scene reconstructionfrom underwater images given its utility for oceanic researchand for recreational image manipulation. In this paperwe propose a novel algorithm for two view camera motionestimation for underwater imagery. Our method leveragesthe constraints provided by the attenuation propertiesof water and its effects on the appearance of the color todetermin
Neural networks designed for real-time object detectionhave recently improved significantly, but in practice, look-ing at only a single RGB image at the time may not be ideal.For example, when detecting objects in videos, a foregrounddetection algorithm can be used to obtain compact temporaldata, which can be fed into a neural network alongside RGBimages. We propose an approach for doing this, bas
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
We derive an expression for the error introduced by the second-order accurate temporal finitedifference (FD) operator, as present in the FD, pseudospectral and spectral element methods for seismic wave modeling applied to time-invariant media. The 'time-dispersion' error speeds up the signal as a function of frequency and time step only. Time dispersion is thus independent of the propagation path,
The iron carbene complex [FeII(btz)3](PF6)2 (where btz = 3,3′-dimethyl-1,1′-bis(p-Tolyl)-4,4′-bis(1,2,3-Triazol-5-ylidene)) has been synthesized, isolated, and characterized as a low-spin ferrous complex. It exhibits strong metal-To-ligand charge transfer (MLCT) absorption bands throughout the visible spectrum, and excitation of these bands gives rise to a 3MLCT state with a 528 ps excited-state l
Amyloid aggregates are associated with a range of human neurodegenerative disorders, and it has been shown that neurotoxicity is dependent on aggregate size. Combining molecular simulation with analytical theory, a predictive model is proposed for the adsorption of amyloid aggregates onto oppositely charged surfaces, where the interaction is governed by an interplay between electrostatic attractio
The excited state dynamics of solvated [Fe(bpy)(CN)4]2-, where bpy = 2,2′-bipyridine, show significant sensitivity to the solvent Lewis acidity. Using a combination of optical absorption and X-ray emission transient spectroscopies, we have previously shown that the metal to ligand charge transfer (MLCT) excited state of [Fe(bpy)(CN)4]2- has a 19 picosecond lifetime and no discernable contribution
In this paper we present new techniques for constructing compact and robust minimal solvers for absolute pose estimation. We focus on the P4Pfr problem, but the methods we propose are applicable to a more general setting. Previous approaches to P4Pfr suffer from artificial degeneracies which come from their formulation and not the geometry of the original problem. In this paper we show how to avoi
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
To be able to determine the position of a static object in 3D space by means of computer vision, it has to be seen by cameras from at least two different view points. The same applies for measuring the position of a moving object based on images captured at one single time instant. However, if the cameras are not synchronized in time, or if a moving object is not visible in all images, one can not
Background: We have previously reported quantitative exposure-response relationships between physical exposures recorded by technical methods, and complaints and diagnoses in the neck/shoulders, and the elbows/hands, based on group data. In the present study the number of workers was doubled, and information on individual factors, and psychosocial working conditions was used. Relationships between
