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Minimal Structure and Motion Problems for TOA and TDOA Measurements with Collinearity Constraints

Structure from sound can be phrased as the problem of determining the position of a number of microphones and a number of sound sources given only the recorded sounds. In this paper we study minimal structure from sound problems in both TOA (time of arrival) and TDOA (time difference of arrival) settings with collinear constraints on e.g. the microphone positions. Three such minimal cases are anal

Pseudo-Boolean Optimization: Theory and Applications in Vision

Many problems in computer vision, such as stereo, segmentation and denoising can be formulated as pseudo-boolean optimization problems. Over the last decade, graphs cuts have become a standard tool for solving such problems. The last couple of years have seen a great advancement in the methods used to minimize pseudoboolean functions of higher order than quadratic. In this paper, we give an overvi

Polynomial Solvers for Geometric Problems - Applications in Computer Vision and Sensor Networks

Given images of a scene taken by a moving camera or recordings of a moving smart phone playing a song by a microphone array, how hard is it to reconstruct the scene structure or the moving trajectory of the phone? In this thesis, we study and solve several fundamental geometric problems in order to provide solutions to these problems. The key underlying technique for solving such geometric probl

Planar Motion and Hand-Eye Calibration Using Inter-Image Homographies from a Planar Scene

In this paper we consider a mobile platform performing partial hand-eye calibration and Simultaneous Localisation and Mapping (SLAM) using images of the floor along with the assumptions of planar motion and constant internal camera parameters. The method used is based on a direct parametrisation of the camera motion, combined with an iterative scheme for determining the motion parameters from inte

Computing with Python

Description: Python® is a free open-source language and environment that has great potential in scientific computing. Computing with Python presents the programming language in close connection wit mathematical applications. The approach of the book is concept based rather than a systematic introduction to the language. It is written for a mathematical readership and is aimed at students with a ma

Applications of Machine Vision — Quality Control, Cancer Detection and Traffic Surveillance

During the last decades, image analysis has become an important tool in various applications. The increase in computer power has led to that more advances algorithms can be developed. In this thesis image analysis has been used in three different applications; quality control of asphalt, cancer detection in histopathological images and traffic surveillance. In the first part of the thesis image a

MINIMAL SOLUTIONS FOR DUAL MICROPHONE RIG SELF-CALIBRATION

In this paper, we study minimal problems related to dual microphone rig self-calibration using TOA measurements from sound sources with unknown positions. We consider the problems with varying setups as (i) if the internal distances between the microphone nodes are known a priori or not. (ii) if the microphone rigs lies in an affine space with different dimension than the sound sources. Solving th

Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project

Global fire-vegetation models are widely used to assess impacts of environmental change on fire regimes and the carbon cycle and to infer relationships between climate, land use and fire. However, differences in model structure and parameterizations, in both the vegetation and fire components of these models, could influence overall model performance, and to date there has been limited evaluation

The GGCMI Phase 2 experiment : Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)

Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. How

Differentiable fixed-rank regularisation using bilinear parameterisation

Low rank structures are present in many applications of computer vision and machine learning. A popular approach consists of explicitly parameterising the set or matrices with sought rank, leading to a bilinear factorisation, reducing the problem to find the bilinear factors. While such an approach can be efficiently implemented using second-order methods, such as Levenberg-Marquardt (LM) or Varia

Upgrade Methods for Stratified Sensor Network Self-Calibration

Estimating receiver and sender positions is often solved using a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. The second step can be seen as an affine upgrade. This affine upgrade is the focus of this paper. In the paper new efficient algorithms for solving for the upgrade parameters using minimal data are presented. It is als

Global climate response to idealized deforestation in CMIP6 models

Changes in forest cover have a strong effect on climate through the alteration of surface biogeophysical and biogeochemical properties that affect energy, water and carbon exchange with the atmosphere. To quantify biogeophysical and biogeochemical effects of deforestation in a consistent setup, nine Earth system models (ESMs) carried out an idealized experiment in the framework of the Coupled Mode

Vegetation demographics in Earth System Models : A review of progress and priorities

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of eco

The End of Law and Other Miracles : On the Limitations of Apocalyptic Political Theologies

This article explores various attempts to critique the law with reference to an authority or idea that is seen as transcending law in its existing forms. As heuristic tools, I use a distinction be-tween prophetic and apocalyptic discourses, the former referring to discourses that remain scep-tical to the possibility of suspending law in any absolute sense; the latter describing discourses that art

Prophetic Political Theology : Daniel Bensaïd's Alternative Radicalism

This article probes the writings of the Jewish Trotskyist thinker Daniel Bensaïd (1946–2010) in light of recent debates on political theology. In contrast to what is sometimes explicitly referred to as ‘apocalyptic political theology’, it makes a case for what may be described as a ‘prophetic political theology’. Yet it is not obvious to claim Bensaïd as a proponent for such a project, since he ex

Deep network for the integrated 3D sensing of multiple people in natural images

We present MubyNet - a feed-forward, multitask, bottom up system for the integrated localization, as well as 3d pose and shape estimation, of multiple people in monocular images. The challenge is the formal modeling of the problem that intrinsically requires discrete and continuous computation, e.g. grouping people vs. predicting 3d pose. The model identifies human body structures (joints and limb