427 research outputs found

    Individualized Models of Colour Differentiation through Situation-Specific Modelling

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    In digital environments, colour is used for many purposes: for example, to encode information in charts, signify missing field information on websites, and identify active windows and menus. However, many people have inherited, acquired, or situationally-induced Colour Vision Deficiency (CVD), and therefore have difficulties differentiating many colours. Recolouring tools have been developed that modify interface colours to make them more differentiable for people with CVD, but these tools rely on models of colour differentiation that do not represent the majority of people with CVD. As a result, existing recolouring tools do not help most people with CVD. To solve this problem, I developed Situation-Specific Modelling (SSM), and applied it to colour differentiation to develop the Individualized model of Colour Differentiation (ICD). SSM utilizes an in-situ calibration procedure to measure a particular user’s abilities within a particular situation, and a modelling component to extend the calibration measurements into a full representation of the user’s abilities. ICD applies in-situ calibration to measuring a user’s unique colour differentiation abilities, and contains a modelling component that is capable of representing the colour differentiation abilities of almost any individual with CVD. This dissertation presents four versions of the ICD and one application of the ICD to recolouring. First, I describe the development and evaluation of a feasibility implementation of the ICD that tests the viability of the SSM approach. Second, I present revised calibration and modelling components of the ICD that reduce the calibration time from 32 minutes to two minutes. Next, I describe the third and fourth ICD versions that improve the applicability of the ICD to recolouring tools by reducing the colour differentiation prediction time and increasing the power of each prediction. Finally, I present a new recolouring tool (ICDRecolour) that uses the ICD model to steer the recolouring process. In a comparative evaluation, ICDRecolour achieved 90% colour matching accuracy for participants – 20% better than existing recolouring tools – for a wide range of CVDs. By modelling the colour differentiation abilities of a particular user in a particular environment, the ICD enables the extension of recolouring tools to helping most people with CVD, thereby reducing the difficulties that people with CVD experience when using colour in digital environments

    Studies on image compression and image reconstruction

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    During this six month period our works concentrated on three, somewhat different areas. We looked at and developed a number of error concealment schemes for use in a variety of video coding environments. This work is described in an accompanying (draft) Masters thesis. In the thesis we describe application of this techniques to the MPEG video coding scheme. We felt that the unique frame ordering approach used in the MPEG scheme would be a challenge to any error concealment/error recovery technique. We continued with our work in the vector quantization area. We have also developed a new type of vector quantizer, which we call a scan predictive vector quantization. The scan predictive VQ was tested on data processed at Goddard to approximate Landsat 7 HRMSI resolution and compared favorably with existing VQ techniques. A paper describing this work is included. The third area is concerned more with reconstruction than compression. While there is a variety of efficient lossless image compression schemes, they all have a common property that they use past data to encode future data. This is done either via taking differences, context modeling, or by building dictionaries. When encoding large images, this common property becomes a common flaw. When the user wishes to decode just a portion of the image, the requirement that the past history be available forces the decoding of a significantly larger portion of the image than desired by the user. Even with intelligent partitioning of the image dataset, the number of pixels decoded may be four times the number of pixels requested. We have developed an adaptive scanning strategy which can be used with any lossless compression scheme and which lowers the additional number of pixels to be decoded to about 7 percent of the number of pixels requested! A paper describing these results is included

    Using genetic algorithms to take into account user wishes in an advanced building control system

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    From a sustainable development perspective, the newly developed automatic controllers for building services are very promising in that they increase energy efficiency and reduce commissioning and maintenance costs. But a major problem has appeared as the automatic building control systems have been implemented: the user rejection of this kind of system is quite high. This is mainly due to a lack of user considerations in the controllers. An integrated blind, electric lighting and heating control system that adapts to user wishes on a long-term basis has been developed in this work to deal with this issue. The adaptation of the control system to user wishes was achieved by means of Genetic Algorithms. They have been seen to be the most appropriate optimization method for this task. They ensure a 100% convergence whereas standard search methods such as Gauss-Newton and Nelder-Mead converge in less than 25% of the time and Simulated Annealing method converges in about 75% of the time. In addition, simulations with a consistent virtual user have shown that the user adaptive controller is capable of anticipation. Nine months of experimental tests were carried out in 14 office rooms of the LESO building with a total of 23 users concerned. Three controllers were compared: a manual control system, an automatic controller without user adaptation and an automatic controller with user adaptation. Tests were conducted in a similar fashion as clinical randomized trials are carried out: control systems are randomly attributed to rooms and users do not know which system they have (single-blind study). Results show that the automatic control rejection percentage is greatly reduced with the user adaptive system. Indeed, after four weeks with an automatic control, 25% of the users with the non-adaptive system reject the automatic control, whereas only 5% of the users with the user adaptive system reject it. These percentages depend neither on age or gender of the user, nor on the number of occupants in a room. Moreover, the energy savings due to automatic control (26% compared to a manual system) are not reduced by the user adaptation. These large energy savings are mainly due to the predictive feature of the heating controller and to the efficient control of electric lighting. In addition, indoor comfort is slightly improved by the automatic controllers for both thermal and visual aspects. The indoor comfort is even slightly more improved by the user adaptive control compared to the non-adaptive one. The user adaptation has not converged properly in the mechanical workshop, a space used by several persons and also considered in the experiments. It has been concluded that user adaptive systems are probably not appropriate for places with irregular users, such as workshops, libraries, corridors and all public spaces

    Vision Science and Technology at NASA: Results of a Workshop

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    A broad review is given of vision science and technology within NASA. The subject is defined and its applications in both NASA and the nation at large are noted. A survey of current NASA efforts is given, noting strengths and weaknesses of the NASA program
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