Real time motion estimation using a neural architecture implemented on GPUs

This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer vision tasks such as image segmentation, object representation or characterization, motion analysis and tracking. The use of a neural network architecture allows for the simultaneous estimation of global and local motion and the representation of deformable objects. This architecture also avoids the problem of finding corresponding features while tracking moving objects. Due to the parallel nature of neural networks, the architecture has been implemented on GPUs that allows the system to meet a set of requirements such as: time constraints management, robustness, high processing speed and re-configurability. Experiments are presented that demonstrate the validity of our architecture to solve problems of mobile agents tracking and motion analysis.

3D-based reconstruction using growing neural gas landmark: application to rapid prototyping in shoe last manufacturing

Customizing shoe manufacturing is one of the great challenges in the footwear industry. It is a production model change where design adopts not only the main role, but also the main bottleneck. It is therefore necessary to accelerate this process by improving the accuracy of current methods. Rapid prototyping techniques are based on the reuse of manufactured footwear lasts so that they can be modified with CAD systems leading rapidly to new shoe models. In this work, we present a shoe last fast reconstruction method that fits current design and manufacturing processes. The method is based on the scanning of shoe last obtaining sections and establishing a fixed number of landmarks onto those sections to reconstruct the shoe last 3D surface. Automated landmark extraction is accomplished through the use of the self-organizing network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates up to 12 times the surface reconstruction and filtering processes used by the current shoe last design software. The proposed method offers higher accuracy compared with methods with similar efficiency as voxel grid.

Methodology based on registration techniques for representing subjects and their deformations acquired from general purpose 3D sensors

In this thesis a methodology for representing 3D subjects and their deformations in adverse situations is studied. The study is focused in providing methods based on registration techniques to improve the data in situations where the sensor is working in the limit of its sensitivity. In order to do this, it is proposed two methods to overcome the problems which can difficult the process in these conditions. First a rigid registration based on model registration is presented, where the model of 3D planar markers is used. This model is estimated using a proposed method which improves its quality by taking into account prior knowledge of the marker. To study the deformations, it is proposed a framework to combine multiple spaces in a non-rigid registration technique. This proposal improves the quality of the alignment with a more robust matching process that makes use of all available input data. Moreover, this framework allows the registration of multiple spaces simultaneously providing a more general technique. Concretely, it is instantiated using colour and location in the matching process for 3D location registration.

Targetless image-based method for measuring displacements and strains on concrete surfaces with a consumer camera

Measurement of concrete strain through non-invasive methods is of great importance in civil engineering and structural analysis. Traditional methods use laser speckle and high quality cameras that may result too expensive for many applications. Here we present a method for measuring concrete deformations with a standard reflex camera and image processing for tracking objects in the concretes surface. Two different approaches are presented here. In the first one, on-purpose objects are drawn on the surface, while on the second one we track small defects on the surface due to air bubbles in the hardening process. The method has been tested on a concrete sample under several loading/unloading cycles. A stop-motion sequence of the process has been captured and analyzed. Results have been successfully compared with the values given by a strain gauge. Accuracy of our methods in tracking objects is below 8 μm, in the order of more expensive commercial devices.

Human Behaviour Recognition based on Trajectory Analysis using Neural Networks

Automated human behaviour analysis has been, and still remains, a challenging problem. It has been dealt from different points of views: from primitive actions to human interaction recognition. This paper is focused on trajectory analysis which allows a simple high level understanding of complex human behaviour. It is proposed a novel representation method of trajectory data, called Activity Description Vector (ADV) based on the number of occurrences of a person is in a specific point of the scenario and the local movements that perform in it. The ADV is calculated for each cell of the scenario in which it is spatially sampled obtaining a cue for different clustering methods. The ADV representation has been tested as the input of several classic classifiers and compared to other approaches using CAVIAR dataset sequences obtaining great accuracy in the recognition of the behaviour of people in a Shopping Centre.

Integrated architecture for vision-based indoor localization and mapping of a quadrotor micro-air vehicle

Atualmente os sistemas de pilotagem autónoma de quadricópteros estão a ser desenvolvidos de forma a efetuarem navegação em espaços exteriores, onde o sinal de GPS pode ser utilizado para definir waypoints de navegação, modos de position e altitude hold, returning home, entre outros. Contudo, o problema de navegação autónoma em espaços fechados sem que se utilize um sistema de posicionamento global dentro de uma sala, subsiste como um problema desafiante e sem solução fechada. Grande parte das soluções são baseadas em sensores dispendiosos, como o LIDAR ou como sistemas de posicionamento externos (p.ex. Vicon, Optitrack). Algumas destas soluções reservam a capacidade de processamento de dados dos sensores e dos algoritmos mais exigentes para sistemas de computação exteriores ao veículo, o que também retira a componente de autonomia total que se pretende num veículo com estas características. O objetivo desta tese pretende, assim, a preparação de um sistema aéreo não-tripulado de pequeno porte, nomeadamente um quadricóptero, que integre diferentes módulos que lhe permitam simultânea localização e mapeamento em espaços interiores onde o sinal GPS ´e negado, utilizando, para tal, uma câmara RGB-D, em conjunto com outros sensores internos e externos do quadricóptero, integrados num sistema que processa o posicionamento baseado em visão e com o qual se pretende que efectue, num futuro próximo, planeamento de movimento para navegação. O resultado deste trabalho foi uma arquitetura integrada para análise de módulos de localização, mapeamento e navegação, baseada em hardware aberto e barato e frameworks state-of-the-art disponíveis em código aberto. Foi também possível testar parcialmente alguns módulos de localização, sob certas condições de ensaio e certos parâmetros dos algoritmos. A capacidade de mapeamento da framework também foi testada e aprovada. A framework obtida encontra-se pronta para navegação, necessitando apenas de alguns ajustes e testes.

Abundance and opal input of radiolarian species of two sediment cores from the Atlantic sector of the Southern Ocean

Radiolarian-based paleoceanographic reconstructions generally use the abundance of selected radiolarian species. However, the recent focus on the opal flux and the development of isotope measurements in biogenic opal and the organic matter embedded in it demands a better knowledge of the origin of the opal. We present here an estimation of the opal content of the skeleton of 63 radiolarian species from two sites in the Southern Ocean. The skeletons are modelled as associations of simple geometrical shapes, and the volume thus obtained is combined with opal density to obtain the amount of opal. These data are, thus, used to determine the most important opal carriers in the radiolarian assemblage in both cores.

Graph-based Semi-Supervised Learning in Acoustic Modeling for Automatic Speech Recognition

Thesis (Ph.D.)--University of Washington, 2016-06

Modelling the input-output behaviour of piezoelectric structural health monitoring systems for composite plates

This paper investigates the input-output characteristics of structural health monitoring systems for composite plates based on permanently attached piezoelectric transmitter and sensor elements. Using dynamic piezoelectricity theory and a multiple integral transform method to describe the propagating and scattered flexural waves an electro-mechanical model for simulating the voltage input-output transfer function for circular piezoelectric transmitters and sensors adhesively attached to an orthotropic composite plate is developed. The method enables the characterization of all three physical processes, i.e. wave generation, wave propagation and wave reception. The influence of transducer, plate and attached electrical circuit characteristics on the voltage output behaviour of the system is examined through numerical calculations, both in frequency and the time domain. The results show that the input-output behaviour of the system is not properly predicted by the transducers' properties alone. Coupling effects between the transducers and the tested structure have to be taken into account, and adding backing materials to the piezoelectric elements can significantly improve the sensitivity of the system. It is shown that in order to achieve maximum sensitivity, particular piezoelectric transmitters and sensors need to be designed according to the structure to be monitored and the specific frequency regime of interest.

Initiation of evasive manoeuvres during self-motion: a test of three hypotheses

To understand performance of evasive and interceptive actions it is important to know how people decide when to initiate a movement - initiating at the 'right' moment is often essential for successful performance. It has been proposed that initiation is triggered when a perceptually derived quantity reaches an invariant criterion value. Candidate quantities include time-to-collision (TTC), distance, and rate of image expansion ( ROE), all of which have received empirical support. We studied initiation of an evasive manoeuvre in a computer-simulated steering task in which the observer was required to steer through a stationary visual environment and avoid colliding with an obstacle in their path. The results could not be explained by hypotheses which propose that evasive manoeuvre initiation is based on a fixed criterion value of TTC or distance. The overall pattern was, however, consistent with the use of a criterion ROE value. This was further tested by analyses designed to directly evaluate whether the ROE value used to initiate the response was the same across experimental conditions. Only two of the six participants showed evidence for using the ROE strategy.

Time motion analysis of 2001 and 2002 super 12 rugby

The aim of this study was to quantify movements of Super 12 rugby players in competition because information on elite rugby players' movements is unavailable. Players were categorized into forwards [front (n = 16) and back row (n = 15)] and backs [inside (n = 9) and outside backs (n = 7)] and their movements analysed by video-based time motion analysis. Movements were classified as rest (standing, walking and jogging) and work (striding, sprinting, static exertion, jumping, lifting or tackling). The total time, number and duration of individual activities were assessed, with differences between groups evaluated using independent sample t-tests (unequal variances), while differences between halves were assessed with paired sample t-tests. Forwards had 7:47 min:s (95% confidence limits: 6:39 to 8:55 min:s, P

Numerical evaluation of the fields induced by body motion in or near high-field MRI scanners

In modern magnetic resonance imaging, both patients and health care workers are exposed to strong. non-uniform static magnetic fields inside and outside of the scanner. In which body movement may be able to induce electric currents in tissues which could be potentially harmful. This paper presents theoretical investigations into the spatial distribution of induced E-fields in a tissue-equivalent human model when moving at various positions around the magnet. The numerical calculations are based on an efficient. quasi-static, finite-difference scheme. Three-dimensional field profiles from an actively shielded 4 T magnet system are used and the body model projected through the field profile with normalized velocity. The simulation shows that it is possible to induce E-fields/currents near the level of physiological significance under some circumstances and provides insight into the spatial characteristics of the induced fields. The methodology presented herein can be extrapolated to very high field strengths for the evaluation of the effects of motion at a variety of field strengths and velocities. (C) 2004 Elsevier Ltd. All rights reserved.

Prediction of slurry transport in SAG mills using SPH fluid flow in a dynamic DEM based porous media

DEM modelling of the motion of coarse fractions of the charge inside SAG mills has now been well established for more than a decade. In these models the effect of slurry has broadly been ignored due to its complexity. Smoothed particle hydrodynamics (SPH) provides a particle based method for modelling complex free surface fluid flows and is well suited to modelling fluid flow in mills. Previous modelling has demonstrated the powerful ability of SPH to capture dynamic fluid flow effects such as lifters crashing into slurry pools, fluid draining from lifters, flow through grates and pulp lifter discharge. However, all these examples were limited by the ability to model only the slurry in the mill without the charge. In this paper, we represent the charge as a dynamic porous media through which the SPH fluid is then able to flow. The porous media properties (specifically the spatial distribution of porosity and velocity) are predicted by time averaging the mill charge predicted using a large scale DEM model. This allows prediction of transient and steady state slurry distributions in the mill and allows its variation with operating parameters, slurry viscosity and slurry volume, to be explored. (C) 2006 Published by Elsevier Ltd.

Incentive-based approaches to sustainable fisheries

The failures of traditional target-species management have led many to propose an ecosystem approach to fisheries to promote sustainability. The ecosystem approach is necessary, especially to account for fishery-ecosystem interactions, but by itself is not sufficient to address two important factors contributing to unsustainable fisheries: inappropriate incentives bearing on fishers and the ineffective governance that frequently exists in commercial, developed fisheries managed primarily by total-harvest limits and input controls. We contend that much greater emphasis must be placed on fisher motivation when managing fisheries. Using evidence from more than a dozen natural experiments in commercial fisheries, we argue that incentive-based approaches that better specify community and individual harvest or territorial rights and price ecosystem services and that are coupled with public research, monitoring, and effective oversight promote sustainable fisheries.

Molecular motors-based micro- and nano-biocomputation devices

Protein molecular motors, which are natural nano-machines that convert the chemical energy into mechanical work for cellular motion, muscle contraction and cell division, have been integrated in the last decade in primitive nanodevices based on the motility of nano-biological objects in micro- and nano-fabricated structures. However, the motility of microorganisms powered by molecular motors has not been similarly exploited. Moreover, among the proposed devices based on molecular motors, i.e., nanosensors, nano-mechanical devices and nano-imaging devices, biocomputation devices are conspicuously missing. The present contribution discusses, based on the present state of the art nano- and micro-fabrication, the comparative advantages and disadvantages of using nano- and micro-biological objects in future computation devices. (c) 2006 Elsevier B.V. All rights reserved.