Plenoptic Signal Processing for Robust Vision in Field Robotics

This thesis proposes the use of plenoptic cameras for improving the robustness and simplicity of machine vision in field robotics applications. Dust, rain, fog, snow, murky water and insufficient light can cause even the most sophisticated vision systems to fail. Plenoptic cameras offer an appealing alternative to conventional imagery by gathering significantly more light over a wider depth of field, and capturing a rich 4D light field structure that encodes textural and geometric information. The key contributions of this work lie in exploring the properties of plenoptic signals and developing algorithms for exploiting them. It lays the groundwork for the deployment of plenoptic cameras in field robotics by establishing a decoding, calibration and rectification scheme appropriate to compact, lenslet-based devices. Next, the frequency-domain shape of plenoptic signals is elaborated and exploited by constructing a filter which focuses over a wide depth of field rather than at a single depth. This filter is shown to reject noise, improving contrast in low light and through attenuating media, while mitigating occluders such as snow, rain and underwater particulate matter. Next, a closed-form generalization of optical flow is presented which directly estimates camera motion from first-order derivatives. An elegant adaptation of this "plenoptic flow" to lenslet-based imagery is demonstrated, as well as a simple, additive method for rendering novel views. Finally, the isolation of dynamic elements from a static background is considered, a task complicated by the non-uniform apparent motion caused by a mobile camera. Two elegant closed-form solutions are presented dealing with monocular time-series and light field image pairs. This work emphasizes non-iterative, noise-tolerant, closed-form, linear methods with predictable and constant runtimes, making them suitable for real-time embedded implementation in field robotics applications

Plenoptic Signal Processing for Robust Vision in Field Robotics

This thesis proposes the use of plenoptic cameras for improving the robustness and simplicity of machine vision in field robotics applications. Dust, rain, fog, snow, murky water and insufficient light can cause even the most sophisticated vision systems to fail. Plenoptic cameras offer an appealing alternative to conventional imagery by gathering significantly more light over a wider depth of field, and capturing a rich 4D light field structure that encodes textural and geometric information. The key contributions of this work lie in exploring the properties of plenoptic signals and developing algorithms for exploiting them. It lays the groundwork for the deployment of plenoptic cameras in field robotics by establishing a decoding, calibration and rectification scheme appropriate to compact, lenslet-based devices. Next, the frequency-domain shape of plenoptic signals is elaborated and exploited by constructing a filter which focuses over a wide depth of field rather than at a single depth. This filter is shown to reject noise, improving contrast in low light and through attenuating media, while mitigating occluders such as snow, rain and underwater particulate matter. Next, a closed-form generalization of optical flow is presented which directly estimates camera motion from first-order derivatives. An elegant adaptation of this "plenoptic flow" to lenslet-based imagery is demonstrated, as well as a simple, additive method for rendering novel views. Finally, the isolation of dynamic elements from a static background is considered, a task complicated by the non-uniform apparent motion caused by a mobile camera. Two elegant closed-form solutions are presented dealing with monocular time-series and light field image pairs. This work emphasizes non-iterative, noise-tolerant, closed-form, linear methods with predictable and constant runtimes, making them suitable for real-time embedded implementation in field robotics applications

Flowing matter

This open access book, published in the Soft and Biological Matter series, presents an introduction to selected research topics in the broad field of flowing matter, including the dynamics of fluids with a complex internal structure -from nematic fluids to soft glasses- as well as active matter and turbulent phenomena.Flowing matter is a subject at the crossroads between physics, mathematics, chemistry, engineering, biology and earth sciences, and relies on a multidisciplinary approach to describe the emergence of the macroscopic behaviours in a system from the coordinated dynamics of its microscopic constituents.Depending on the microscopic interactions, an assembly of molecules or of mesoscopic particles can flow like a simple Newtonian fluid, deform elastically like a solid or behave in a complex manner. When the internal constituents are active, as for biological entities, one generally observes complex large-scale collective motions. Phenomenology is further complicated by the invariable tendency of fluids to display chaos at the large scales or when stirred strongly enough. This volume presents several research topics that address these phenomena encompassing the traditional micro-, meso-, and macro-scales descriptions, and contributes to our understanding of the fundamentals of flowing matter.This book is the legacy of the COST Action MP1305 “Flowing Matter”

Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking

In this paper, we propose a generative framework that unifies depth-based 3D facial pose tracking and face model adaptation on-the-fly, in the unconstrained scenarios with heavy occlusions and arbitrary facial expression variations. Specifically, we introduce a statistical 3D morphable model that flexibly describes the distribution of points on the surface of the face model, with an efficient switchable online adaptation that gradually captures the identity of the tracked subject and rapidly constructs a suitable face model when the subject changes. Moreover, unlike prior art that employed ICP-based facial pose estimation, to improve robustness to occlusions, we propose a ray visibility constraint that regularizes the pose based on the face model's visibility with respect to the input point cloud. Ablation studies and experimental results on Biwi and ICT-3DHP datasets demonstrate that the proposed framework is effective and outperforms completing state-of-the-art depth-based methods

Open-Wheel Aerodynamics: Effects of Tyre Deformation and Internal Flow

Competitive performance of an F1 race car relies upon a well designed and highly developed aerodynamic system. In order to achieve this, total understanding of the downstream wake of exposed rotating wheels is essential. Components such as bargeboards and indeed much of the front wing are developed to provide pressure gradients and vortex structures to influence the wheel wake, ensuring high energy mass-flow to the sensitive leading edge of the underfloor and eventually the rear wing. Wind tunnel testing of model-scale deformable tyres has become a common occurrence in F1 in recent years although there is a significant lack of available literature, academic or otherwise, as to their use. This work has studied in detail the aerodynamic consequences which occur from the varying sidewall bulge and contact patch region making use of several techniques. These include scanning rotating tyre profiles under load, static contact patch size measurements, five-hole pressure probe wake measurements, particle image velocimetry (PIV) and load-cell drag measurements. CFD simulations utilising two industrial codes have also been performed to support the experimental work. Coordinates representing tyre profiles under a range of on-track conditions are available for other researchers to use as a basis for CFD studies. The work presented here includes a full range of representative on-track axle heights which far exceed the more conservative range usually tested in an industrial setting for longevity reasons. The most sensitive parameters for aerodynamic testing of wheels have been identified. For development of a full car, in decreasing order of priority, the following must be correctly matched to the realistic scenario: axle height, yaw condition (without glycerol - often used to reduce friction at the expense of a compromised tyre profile), camber angle, detailed internals, high inflation pressure, through-hub flow rate and least significantly the rotation of the internal brake rotor. The study of through-hub flows revealed that the external aerodynamic effect of the brake scoop inlet varies significantly with the amount of internal restriction. The pumping effect of the brake rotor was measured to be negligible compared to the restrictive effect of its internal passages and that leads to an effect known as inlet spillage with a negative cooling drag trend, whereby the drag of the wheel assembly decreases with increased through-hub flow

Localization and Optimization Problems for Camera Networks

In the framework of networked control systems, we focus on networks of autonomous PTZ cameras. A large set of cameras communicating each other through a network is a widely used architecture in application areas like video surveillance, tracking and motion. First, we consider relative localization in sensor networks, and we tackle the issue of investigating the error propagation, in terms of the mean error on each component of the optimal estimator of the position vector. The relative error is computed as a function of the eigenvalues of the network: using this formula and focusing on an exemplary class of networks (the Abelian Cayley networks), we study the role of the network topology and the dimension of the networks in the error characterization. Second, in a network of cameras one of the most crucial problems is calibration. For each camera this consists in understanding what is its position and orientation with respect to a global common reference frame. Well-known methods in computer vision permit to obtain relative positions and orientations of pairs of cameras whose sensing regions overlap. The aim is to propose an algorithm that, from these noisy input data makes the cameras complete the calibration task autonomously, in a distributed fashion. We focus on the planar case, formulating an optimization problem over the manifold SO(2). We propose synchronous deterministic and distributed algorithms that calibrate planar networks exploiting the cycle structure of the underlying communication graph. Performance analysis and numerical experiments are shown. Third, we propose a gossip-like randomized calibration algorithm, whose probabilistic convergence and numerical studies are provided. Forth and finally, we design surveillance trajectories for a network of calibrated autonomous cameras to detect intruders in an environment, through a continuous graph partitioning problem

Traversing SPIV for the measurement of vortex rings under background rotation

This thesis describes the statistical measurement of vortex ring velocity elds. The measurements were conducted using high accuracy SPIV, with the measurement system traversing with the vortex ring. This incurred two sources of error: vibration led to the superposition of a fluctuating bias across the entire velocity frame; motion of the cameras over time gave rise to inaccuracies in the camera calibration, thus a registration error. Furthermore vortex rings' trajectories carried them away from the centre of the light sheet. The development, implementation and basic evaluation of the corrections to the velocity eld to account for these problems (which showed an overall improvement) was a significant undertaking and constitutes a major portion of the work. The vortex ring measurements were performed on the University of Warwick's recently commissioned unique, large scale, geophysical vortex facility. This enabled measurement of the vortex rings inside a rotating environment and the effects of Coriolis force upon discrete vortex structures to be investigated. Through consideration of the mean velocity elds for non-rotating vortex rings and the properties derived thereof (trajectory, diameter, circulation, core diameter), several flow phenomena are discussed: the axial swirling flow seen by Naitoh et al. (2002) is shown to vary across a wide range of values and tentative support presented for the existence of differing classes of turbulent vortex rings (Dziedzic and Leutheusser, 2004). Analysis of similar properties for vortex rings produced under background rotation, as well as reinterpretation of numerical results presented by Verzicco et al. (1996) (the single prior work on the subject), leads to a detailed description of the dynamics of the velocity eld evolution. In addition, it is shown that nondimensionalising time evolution curves of vortex ring trajectory and circulation cause data collapse across a range of generation conditions and rotation rates

Thermal performance analysis of advanced cooling passages for gas turbine blades

The Ph.D. project here presented aimed at the design and realization of a rotating test rig for heat transfer measurements on internal cooling passages of gas turbine blades, with the final purpose to apply the developed heat transfer measurement methodology on a realistic geometry of blade cooling channels. The transient thermocromic liquid crystals (TLC) technique has been used for the measurements. This technique had to be adapted to the requirements of the test rig, hence allowing measurements in rotating conditions and with different temperature step evolutions imposed to the process fluid. Indeed, the adopted technique is based on the imposition of a temperature step on the fluid that laps the measurement surface, previously painted with thermocromic liquid crystals. The analysis of the surface temperature evolution given by the indication of the liquid crystals allows the evaluation of the surface heat transfer coefficient, that is a direct indicator of the heat transfer distribution of the analyzed surface. In order to replicate the same buoyancy effects induced on the flow by the Coriolis forces during rotation on this complex geometry, the transient measurements are performed with a cold temperature step on the coolant flow. The validation of both rig and methodology has been performed by tests on a simplified geometry of cooling channel, namely a square channel whit ribs normal to the flow direction installed only on a single wall. Liquid crystals with different activation temperatures were used. In order to stress the measurement chain, hence assess the reliability of the measurements, different temperature evolutions were imposed to the process fluid, also varying the rotating conditions. Test on a realistic cooling geometry were performed at different rotating conditions. The cooling scheme is made up of three passages connected by two 180 degree bend. Each passage has different aspect ratio and turbulent promoters configuration, also at the end of the first passage and along the trailing edge a flow extraction is imposed. In this thesis, the rig design and working principle are presented in details. In particular, the solutions adopted to generate the sudden cold temperature step, acquire the experimental data on board of the rotating test model and to control the experimental parameters during tests execution are described. The last chapters are dedicated to the presentation of the validation test and to comment the first results obtained on a realistic cooling channel geometry

Deformable 3-D Modelling from Uncalibrated Video Sequences

Submitted for the degree of Doctor of Philosophy, Queen Mary, University of Londo