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Indoor positioning for smart phone users has received a lot of attention in recent years. While many solutions have been developed, most rely on extra sensors, a need for predeployment of infrastructure or collecting ground truth data to train on. In this paper we see what can be done using only existing WiFi-infrastructure and Received Signal Strength from these, not using any extra sensors or ca
In this paper we present a system for performing low rank matrix factorization. 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. We specifically target structured data patterns, with outliers and large amounts of missing data. Using recently
Data assimilation methods provide a rigorous statistical framework for constraining parametric uncertainty in land surface models (LSMs), which in turn helps to improve their predictive capability and to identify areas in which the representation of physical processes is inadequate. The increase in the number of available datasets in recent years allows us to address different aspects of the model
In this paper we study symmetries in polynomial equation systems and how they can be integrated into the action matrix method. The main contribution is a generalization of the partial p-fold symmetry and we provide new theoretical insights as to why these methods work. We show several examples of how to use this symmetry to construct more compact polynomial solvers. As a second contribution we pre
In this paper, we focus on solving the time delay as a separateproblem to the reconstruction of the microphone and sound locations.The time delay estimation appears as one of the main steps in sensorcalibration problem, once the time delays are known or estimated, wecan solve the time-difference-of-arrival problems by converting them totime-of-arrival problems. In this paper we make use of an alte
In this paper we present a novel, fast and accurate system for detecting the presence of cars in parking lots. The system is based on fast integral channel features and machine learning. The methods are well suited for running embedded on low performance platforms. The methods are tested on a database of nearly 700,000 images of parking spaces, where 48.5% are occupied and the rest are free. The e
We present a minimal solver for a special kind of homography arising in applications with planar camera motion (e.g. mobile robotics applications). Since the camera motion we consider only has five degrees of freedom, an explicit parametrisation allows us to reduce the required number of point correspondences to 2.5. Using fewer point correspondences is beneficial when used together with RANSAC, b
Motivation: Dynamical models describing intracellular phenomena are increasing in size and complexity as more information is obtained from experiments. These models are often over-parameterized with respect to the quantitative data used for parameter estimation, resulting in uncertainty in the individual parameter estimates as well as in the predictions made from the model. Here we combine Bayesia
A tropical maritime case of deep convective clouds was studied using a state-of-the-art aerosol-cloud model in order to evaluate the microphysical mechanisms of aerosol indirect effects (AIE). The aerosol-cloud scheme used is a hybrid bin/bulk model, which treats all phases of clouds and precipitation allowing a detailed analysis of process
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
High-precision analyses of the isotopic composition of methane in ambient air can potentially be used to discriminate between different source categories. Due to the complexity of isotope ratio measurements, such analyses have generally been performed in the laboratory on air samples collected in the field. This poses a limitation on the temporal resolution at which the isotopic composition can be
Inthispaper,wedescribeanovelsystemthatidentifiesrelationsbetweentheobjectsextractedfromanimage. We started from the idea that in addition to the geometric and visual properties of the image objects, we could exploit lexical and semantic information from the text accompanying the image. As experimental set up, we gathered a corpus of images from Wikipedia as well as their associated articles. We ex
In this paper, we describe a system that jointly extracts entities appearing in images and mentioned in their ac- companying captions. As input, the entity linking pro- gram takes a segmented image together with its cap- tion. It consists of a sequence of processing steps: part- of-speech tagging, dependency parsing, and coreference resolution that enables us to identify the entities as well as po
This paper describes a set of methods to link entities across images and text. As a corpus, we used a data set of images, where each image is commented by a short caption and where the regions in the images are manually segmented and labeled with a category. We extracted the entity mentions from the captions and we computed a semantic similarity between the mentions and the region labels. We also
The purpose of this study is to investigate the interaction between small-scale turbulence and aerosol and cloud microphysical properties using direct numerical simulations (DNS). We consider the domain located at the height of about 2000 m from the sea level, experiencing transient high supersaturation due to atmospheric fluctuations of temperature and humidity. To study the effect of total numbe
Planar motion is an important and frequently occurring situation in mobile robotics applications. This thesis concerns estimation of ego-motion and pose of a single downwards oriented camera under the assumptions of planar motion and known internal camera parameters. The so called essential matrix (or its uncalibrated counterpart, the fundamental matrix) is frequently used in computer vision appli
Year-to-year variations in the atmospheric methane (CH4) growth rate show significant correlation with climatic drivers. The second half of 2010 and the first half of 2011 experienced the strongest La Niña since the early 1980s, when global surface networks started monitoring atmospheric CH4 mole fractions. We use these surface measurements, retrievals of column-averaged CH4 mole fractions from GO
N2O is currently the third most important anthropogenic greenhouse gas in terms of radiative forcing and its atmospheric mole fraction is rising steadily. To quantify the growth rate and its causes over the past decades, we performed a multi-site reconstruction of the atmospheric N2O mole fraction and isotopic composition using new and previously published firn air data collected from Greenland an
