Modelling the human accommodation system using finite element analysis

The human accommodation system has been extensively examined for over a century, with a particular focus on trying to understand the mechanisms that lead to the loss of accommodative ability with age (Presbyopia). The accommodative process, along with the potential causes of presbyopia, are disputed; hindering efforts to develop methods of restoring accommodation in the presbyopic eye. One method that can be used to provide insight into this complex area is Finite Element Analysis (FEA). The effectiveness of FEA in modelling the accommodative process has been illustrated by a number of accommodative FEA models developed to date. However, there have been limitations to these previous models; principally due to the variation in data on the geometry of the accommodative components, combined with sparse measurements of their material properties. Despite advances in available data, continued oversimplification has occurred in the modelling of the crystalline lens structure and the zonular fibres that surround the lens. A new accommodation model was proposed by the author that aims to eliminate these limitations. A novel representation of the zonular structure was developed, combined with updated lens and capsule modelling methods. The model has been designed to be adaptable so that a range of different age accommodation systems can be modelled, allowing the age related changes that occur to be simulated. The new modelling methods were validated by comparing the changes induced within the model to available in vivo data, leading to the definition of three different age models. These were used in an extended sensitivity study on age related changes, where individual parameters were altered to investigate their effect on the accommodative process. The material properties were found to have the largest impact on the decline in accommodative ability, in particular compared to changes in ciliary body movement or zonular structure. Novel data on the importance of the capsule stiffness and thickness was also established. The new model detailed within this thesis provides further insight into the accommodation mechanism, as well as a foundation for future, more detailed investigations into accommodation, presbyopia and accommodative restoration techniques.

Modeling Pulsatility in the Human Cardiovascular System

AMS Subj. Classification: 92C30

Grid-texture mechanisms in human vision:contrast detection of regular sparse micro-patterns requires specialist templates

Previous work has shown that human vision performs spatial integration of luminance contrast energy, where signals are squared and summed (with internal noise) over area at detection threshold. We tested that model here in an experiment using arrays of micro-pattern textures that varied in overall stimulus area and sparseness of their target elements, where the contrast of each element was normalised for sensitivity across the visual field. We found a power-law improvement in performance with stimulus area, and a decrease in sensitivity with sparseness. While the contrast integrator model performed well when target elements constituted 50–100% of the target area (replicating previous results), observers outperformed the model when texture elements were sparser than this. This result required the inclusion of further templates in our model, selective for grids of various regular texture densities. By assuming a MAX operation across these noisy mechanisms the model also accounted for the increase in the slope of the psychometric function that occurred as texture density decreased. Thus, for the first time, mechanisms that are selective for texture density have been revealed at contrast detection threshold. We suggest that these mechanisms have a role to play in the perception of visual textures.

An investigation of the molecular interactions between statins and bacterial pathogens, and their combined impact on the human immune system

Statins are a class of drug that inhibits cholesterol biosynthesis, and are used to treat patients with high serum cholesterol levels. They exert this function by competitively binding to the enzyme 3-hydroxy-3-methylglutaryl-CoenzymeA reductase (HMGR), which catalyses the formation of mevalonate, a rate-limiting step in cholesterol biosynthesis. In addition, statins have what are called “pleiotropic effects”, which include the reduction of inflammation, immunomodulation, and antimicrobial effects. Statins can also improve survival of patients with sepsis and pneumonia. Cystic fibrosis (CF) is the most common recessive inherited disease in the Caucasian population, which is characterised by factors including, but not limited to, excessive lung inflammation and increased susceptibility to infection. Therefore, the overall objective of this study was to examine the effects of statins on CFassociated bacterial pathogens and the host response. In this work, the prevalence of HMGR was examined in respiratory pathogens, and several CF-associated pathogens were found to possess homologues of this enzyme. HMGR homology was analysed in Staphylococcus aureus, Burkholderia cenocepacia and Streptococcus pneumoniae, and the HMGR of B. cenocepacia was found to have significant conservation to that of Pseudomonas mevalonii, which is the most widely-characterised bacterial HMGR. However, in silico analysis revealed that, unlike S. aureus and S. pneumoniae, B. cenocepacia did not possess homologues of other mevalonate pathway proteins, and that the HMGR of B. cenocepacia appeared to be involved in an alternative metabolic pathway. The effect of simvastatin was subsequently tested on the growth and virulence of S. aureus, B. cenocepacia and S. pneumoniae. Simvastatin inhibited the growth of all 3 species in a dose-dependent manner. In addition, statin treatment also attenuated biofilm formation of all 3 species, and reduced in vitro motility of S. aureus. Interestingly, simvastatin also increased the potency of the aminoglycoside antibiotic gentamicin against B. cenocepacia. The impact of statins was subsequently tested on the predominant CF-associated pathogen Pseudomonas aeruginosa, which does not possess a HMGR homologue. Mevastatin, lovastatin and simvastatin did not influence the growth of this species. However, sub-inhibitory statin concentrations reduced the swarming motility and biofilm formation of P. aeruginosa. The influence of statins was also examined on Type 3 toxin secretion, quorum sensing and chemotaxis, and no statin effect was observed on any of these phenotypes. Statins did not appear to have a characteristic effect on the P. aeruginosa transcriptome. However, a mutant library screen revealed that the effect of statins on P. aeruginosa biofilm was mediated through the PvrR regulator and the Cup fimbrial biosynthesis genes. Furthermore, proteomic analysis demonstrated that 6 proteins were reproducibly induced by simvastatin in the P. aeruginosa swarming cells. The effect of statins on the regulation of the host-P. aeruginosa immune response was also investigated. Statin treatment increased expression of the pro-inflammatory cytokines IL-8 and CCL20 in lung epithelial cells, but did not attenuate P. aeruginosa-mediated inflammatory gene induction. In fact, simvastatin and P. aeruginosa caused a synergistic effect on CCL20 expression. The expression of the transcriptional regulators KLF2 and KLF6 was also increased by statins and P. aeruginosa, with the induction of KLF6 by simvastatin proving to be a novel effect. Interestingly, both statins and P. aeruginosa were capable of inducing alternative splicing of KLF6. P. aeruginosa was found to induce KLF6 alternative splicing by way of the type 3 secreted toxin ExoS. In addition, a mechanistic role was elucidated for KLF6 in the lung, as it was determined that statin-mediated induction of this protein was responsible for the induction of the host response genes CCL20 and iNOS. Moreover, statin treatment caused a slight increase in infection-related cytotoxicity, and increased bacterial adhesion to cells. Taken together, these data demonstrate that statins can reduce the virulence of CFassociated bacterial pathogens and alter host response effectors. Furthermore, novel statin effectors were identified in both bacterial and host cells.

DESEO: an active vision system for detection, tracking and recognition

[EN]In this paper, a basic conceptual architecture aimed at the design of Computer Vision System is qualitatively described. The proposed architecture addresses the design of vision systems in a modular fashion using modules with three distinct units or components: a processing network or diagnostics unit, a control unit and a communications unit. The control of the system at the modules level is designed based on a Discrete Events Model. This basic methodology has been used to design a realtime active vision system for detection, tracking and recognition of people. It is made up of three functional modules aimed at the detection, tracking, recognition of moving individuals plus a supervision module.

An active vision system integrating fast and slow processes

[EN]This paper describes an Active Vision System whose design assumes a distinction between fast or reactive and slow or background processes. Fast processes need to operate in cycles with critical timeouts that may affect system stability. While slow processes, though necessary, do not compromise system stability if its execution is delayed. Based on this simple taxonomy, a control architecture has been proposed and a prototype implemented that is able to track people in real-time with a robotic head while trying to identify the target. In this system, the tracking module is considered as the reactive part of the system while person identification is considered a background task.

A C80 DSP-based active vision system for real-time tracking

[EN]Active Vision Systems can be considered as dynamical systems which close the loop around artificial visual perception, controlling camera parameters, motion and also controlling processing to simplify, accelerate and do more robust visual perception. Research and Development in Active Vision Systems [Aloi87], [Bajc88] is a main area of interest in Computer Vision, mainly by its potential application in different scenarios where real-time performance is needed such as robot navigation, surveillance, visual inspection, among many others. Several systems have been developed during last years using robotic-heads for this purpose...

Impact of automatic region-of-interest coding on perceived quality in mobile video

At present, the most reliable method to obtain end-user perceived quality is through subjective tests. In this paper, the impact of automatic region-of-interest (ROI) coding on perceived quality of mobile video is investigated. The evidence, which is based on perceptual comparison analysis, shows that the coding strategy improves perceptual quality. This is particularly true in low bit rate situations. The ROI detection method used in this paper is based on two approaches: - (1) automatic ROI by analyzing the visual contents automatically, and; - (2) eye-tracking based ROI by aggregating eye-tracking data across many users, used to both evaluate the accuracy of automatic ROI detection and the subjective quality of automatic ROI encoded video. The perceptual comparison analysis is based on subjective assessments with 54 participants, across different content types, screen resolutions, and target bit rates while comparing the two ROI detection methods. The results from the user study demonstrate that ROI-based video encoding has higher perceived quality compared to normal video encoded at a similar bit rate, particularly in the lower bit rate range.

The Three-Dimensional Interpretation of a Class of Simple Line-Drawings

We provide a theory of the three-dimensional interpretation of a class of line-drawings called p-images, which are interpreted by the human vision system as parallelepipeds ("boxes"). Despite their simplicity, p-images raise a number of interesting vision questions: *Why are p-images seen as three-dimensional objects? Why not just as flatimages? *What are the dimensions and pose of the perceived objects? *Why are some p-images interpreted as rectangular boxes, while others are seen as skewed, even though there is no obvious distinction between the images? *When p-images are rotated in three dimensions, why are the image-sequences perceived as distorting objects---even though structure-from-motion would predict that rigid objects would be seen? *Why are some three-dimensional parallelepipeds seen as radically different when viewed from different viewpoints? We show that these and related questions can be answered with the help of a single mathematical result and an associated perceptual principle. An interesting special case arises when there are right angles in the p-image. This case represents a singularity in the equations and is mystifying from the vision point of view. It would seem that (at least in this case) the vision system does not follow the ordinary rules of geometry but operates in accordance with other (and as yet unknown) principles.

Image segmentation integrating colour, texture and boundary information

La tesis se centra en la Visión por Computador y, más concretamente, en la segmentación de imágenes, la cual es una de las etapas básicas en el análisis de imágenes y consiste en la división de la imagen en un conjunto de regiones visualmente distintas y uniformes considerando su intensidad, color o textura. Se propone una estrategia basada en el uso complementario de la información de región y de frontera durante el proceso de segmentación, integración que permite paliar algunos de los problemas básicos de la segmentación tradicional. La información de frontera permite inicialmente identificar el número de regiones presentes en la imagen y colocar en el interior de cada una de ellas una semilla, con el objetivo de modelar estadísticamente las características de las regiones y definir de esta forma la información de región. Esta información, conjuntamente con la información de frontera, es utilizada en la definición de una función de energía que expresa las propiedades requeridas a la segmentación deseada: uniformidad en el interior de las regiones y contraste con las regiones vecinas en los límites. Un conjunto de regiones activas inician entonces su crecimiento, compitiendo por los píxeles de la imagen, con el objetivo de optimizar la función de energía o, en otras palabras, encontrar la segmentación que mejor se adecua a los requerimientos exprsados en dicha función. Finalmente, todo esta proceso ha sido considerado en una estructura piramidal, lo que nos permite refinar progresivamente el resultado de la segmentación y mejorar su coste computacional. La estrategia ha sido extendida al problema de segmentación de texturas, lo que implica algunas consideraciones básicas como el modelaje de las regiones a partir de un conjunto de características de textura y la extracción de la información de frontera cuando la textura es presente en la imagen. Finalmente, se ha llevado a cabo la extensión a la segmentación de imágenes teniendo en cuenta las propiedades de color y textura. En este sentido, el uso conjunto de técnicas no-paramétricas de estimación de la función de densidad para la descripción del color, y de características textuales basadas en la matriz de co-ocurrencia, ha sido propuesto para modelar adecuadamente y de forma completa las regiones de la imagen. La propuesta ha sido evaluada de forma objetiva y comparada con distintas técnicas de integración utilizando imágenes sintéticas. Además, se han incluido experimentos con imágenes reales con resultados muy positivos.

Episodic Reasoning for Vision-Based Human Action Recognition

Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning.

A Vision Based Target Detection System for Docking of an Autonomous Underwater Vehicle

This paper describes the development and preliminary experimental evaluation of a visionbased docking system to allow an Autonomous Underwater Vehicle (AUV) to identify and attach itself to a set of uniquely identifiable targets. These targets, docking poles, are detected using Haar rectangular features and rotation of integral images. A non-holonomic controller allows the Starbug AUV to orient itself with respect to the target whilst maintaining visual contact during the manoeuvre. Experimental results show the proposed vision system is capable of robustly identifying a pair of docking poles simultaneously in a variety of orientations and lighting conditions. Experiments in an outdoor pool show that this vision system enables the AUV to dock autonomously from a distance of up to 4m with relatively low visibility.

Design of automatic vision-based inspection system for solder joint segmentation

Purpose: Computer vision has been widely used in the inspection of electronic components. This paper proposes a computer vision system for the automatic detection, localisation, and segmentation of solder joints on Printed Circuit Boards (PCBs) under different illumination conditions. Design/methodology/approach: An illumination normalization approach is applied to an image, which can effectively and efficiently eliminate the effect of uneven illumination while keeping the properties of the processed image the same as in the corresponding image under normal lighting conditions. Consequently special lighting and instrumental setup can be reduced in order to detect solder joints. These normalised images are insensitive to illumination variations and are used for the subsequent solder joint detection stages. In the segmentation approach, the PCB image is transformed from an RGB color space to a YIQ color space for the effective detection of solder joints from the background. Findings: The segmentation results show that the proposed approach improves the performance significantly for images under varying illumination conditions. Research limitations/implications: This paper proposes a front-end system for the automatic detection, localisation, and segmentation of solder joint defects. Further research is required to complete the full system including the classification of solder joint defects. Practical implications: The methodology presented in this paper can be an effective method to reduce cost and improve quality in production of PCBs in the manufacturing industry. Originality/value: This research proposes the automatic location, identification and segmentation of solder joints under different illumination conditions.

Human optical axial length and defocus

Purpose: To investigate the short term influence of imposed monocular defocus upon human optical axial length (the distance from anterior cornea to retinal pigment epithelium) and ocular biometrics. Methods: Twenty-eight young adult subjects (14 myopes and 14 emmetropes) had eye biometrics measured before and then 30 and 60 minutes after exposure to monocular (right eye) defocus. Four different monocular defocus conditions were tested, each on a separate day: control (no defocus), myopic (+3 D defocus), hyperopic (-3 D defocus) and diffuse (0.2 density Bangerter filter) defocus. The fellow eye was optimally corrected (no defocus). Results: Imposed defocus caused small but significant changes in optical axial length (p<0.0001). A significant increase in optical axial length (mean change +8 ± 14 μm, p=0.03) occurred following hyperopic defocus, and a significant reduction in optical axial length (mean change -13 ± 14 μm, p=0.0001) was found following myopic defocus. A small increase in optical axial length was observed following diffuse defocus (mean change +6 ± 13 μm, p=0.053). Choroidal thickness also exhibited some significant changes with certain defocus conditions. No significant difference was found between myopes and emmetropes in the changes in optical axial length or choroidal thickness with defocus. Conclusions: Significant changes in optical axial length occur in human subjects following 60 minutes of monocular defocus. The bi-directional optical axial length changes observed in response to defocus implies the human visual system is capable of detecting the presence and sign of defocus and altering optical axial length to move the retina towards the image plane.