5 resultados para Visione Robotica Calibrazione Camera Robot Hand Eye
em Aston University Research Archive
Resumo:
Aim: The aim of this study was to assess the impact of hand washing regimes on lipid transference to contact lenses. The presence of lipids on contact lenses can affect visual acuity and enhance spoilation. Additionally, they may even mediate and foster microbial transfer and serve as a marker of potential dermal contamination. Methods and materials: A social hand wash and the Royal College of Nursing (RCN) hand wash were investigated. A 'no-wash regime' was used as control. The transfer of lipids from the hand was assessed by Thin Layer Chromatography (TLC). Lipid transference to the contact lenses was studied through fluorescence spectroscopy (FS). Results: Iodine staining, for presence of lipids, on TLC plates indicated the 'no-wash regime' score averaged at 3.4 ± 0.8, the social wash averaged at 2.2 ± 0.9 and the RCN averaged at 1.2 ± 0.3 on a scale of 1-4. The FS of lipids on contact lenses for 'no washing' presented an average of 28.47 ± 10.54 fluorescence units (FU), the social wash presented an average of 13.52 ± 11.12. FU and the RCN wash presented a much lower average 6.47 ± 4.26. FU. Conclusions: This work demonstrates how the method used for washing the hands can affect the concentration of lipids, and the transfer of these lipids onto contact lenses. A regime of hand washing for contact lens users should be standardised to help reduce potentially transferable species present on the hands. © 2011 British Contact Lens Association.
Resumo:
In this paper we propose an approach based on self-interested autonomous cameras, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to grow the vision graph during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online which permits the addition and removal cameras to the network during runtime and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multi-camera calibration can be avoided. © 2011 IEEE.
Resumo:
Aim: To determine the theoretical and clinical minimum image pixel resolution and maximum compression appropriate for anterior eye image storage. Methods: Clinical images of the bulbar conjunctiva, palpebral conjunctiva, and corneal staining were taken at the maximum resolution of Nikon:CoolPix990 (2048 × 1360 pixels), DVC:1312C (1280 × 811), and JAI:CV-S3200 (767 × 569) single chip cameras and the JVC:KYF58 (767 × 569) three chip camera. The images were stored in TIFF format and further copies created with reduced resolution or compressed. The images were then ranked for clarity on a 15 inch monitor (resolution 1280 × 1024) by 20 optometrists and analysed by objective image analysis grading. Theoretical calculation of the resolution necessary to detect the smallest objects of clinical interest was also conducted. Results: Theoretical calculation suggested that the minimum resolution should be ≥579 horizontal pixels at 25 × magnification. Image quality was perceived subjectively as being reduced when the pixel resolution was lower than 767 × 569 (p<0.005) or the image was compressed as a BMP or <50% quality JPEG (p<0.005). Objective image analysis techniques were less susceptible to changes in image quality, particularly when using colour extraction techniques. Conclusion: It is appropriate to store anterior eye images at between 1280 × 811 and 767 × 569 pixel resolution and at up to 1:70 JPEG compression.
Resumo:
In this article we present an approach to object tracking handover in a network of smart cameras, based on self-interested autonomous agents, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to learn the vision graph, that is, the camera neighbourhood relations, during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online, enabling efficient deployment in unknown scenarios and camera network topologies, and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multicamera calibration can be avoided. We have evaluated our approach both in a simulation study and in network of real distributed smart cameras.
Resumo:
This thesis describes the design and development of an eye alignment/tracking system which allows self alignment of the eye’s optical axis with a measurement axis. Eye alignment is an area of research largely over-looked, yet it is a fundamental requirement in the acquisition of clinical data from the eye. New trends in the ophthalmic market, desiring portable hand-held apparatus, and the application of ophthalmic measurements in areas other than vision care have brought eye alignment under new scrutiny. Ophthalmic measurements taken in hand-held devices with out an clinician present requires alignment in an entirely new set of circumstances, requiring a novel solution. In order to solve this problem, the research has drawn upon eye tracking technology to monitor the eye, and a principle of self alignment to perform alignment correction. A handheld device naturally lends itself to the patient performing alignment, thus a technique has been designed to communicate raw eye tracking data to the user in a manner which allows the user to make the necessary corrections. The proposed technique is a novel methodology in which misalignment to the eye’s optical axis can be quantified, corrected and evaluated. The technique uses Purkinje Image tracking to monitor the eye’s movement as well as the orientation of the optical axis. The use of two sets of Purkinje Images allows quantification of the eye’s physical parameters needed for accurate Purkinje Image tracking, negating the need for prior anatomical data. An instrument employing the methodology was subsequently prototyped and validated, allowing a sample group to achieve self alignment of their optical axis with an imaging axis within 16.5-40.8 s, and with a rotational precision of 0.03-0.043°(95% confidence intervals). By encompassing all these factors the technique facilitates self alignment from an unaligned position on the visual axis to an aligned position on the optical axis. The consequence of this is that ophthalmic measurements, specifically pachymetric measurements, can be made in the absence of an optician, allowing the use of ophthalmic instrumentation and measurements in health professions other than vision care.