Search for dissertations about: "Low vision"
Showing result 1 - 5 of 220 swedish dissertations containing the words Low vision.
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1. Optics for Low Vision Enabling
Abstract : For people with central visual field loss, eccentric vision is all that they have to rely on. Even for those who learn how to correctly utilize their eccentric vision, it will never be as good as the central for two entirely different reasons: the off-axis optics of the eye can result in large refractive errors, and the low function of the peripheral retina. READ MORE
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2. Peripheral Vision : Adaptive Optics and Psychophysics
Abstract : This thesis is about our peripheral vision. Peripheral vision is poor compared to central vision, due to both neural and optical factors. The optical factors include astigmatism, defocus and higher order aberrations consisting mainly of coma. Neurally, the density of ganglion cells decreases towards the periphery, which limits the sampling density. READ MORE
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3. Embedded high-resolution stereo-vision of high frame-rate and low latency through FPGA-acceleration
Abstract : Autonomous agents rely on information from the surrounding environment to act upon. In the array of sensors available, the image sensor is perhaps the most versatile, allowing for detection of colour, size, shape, and depth. For the latter, in a dynamic environment, assuming no a priori knowledge, stereo vision is a commonly adopted technique. READ MORE
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4. Computational Methods for Computer Vision : Minimal Solvers and Convex Relaxations
Abstract : Robust fitting of geometric models is a core problem in computer vision. The most common approach is to use a hypothesize-and-test framework, such as RANSAC. In these frameworks the model is estimated from as few measurements as possible, which minimizes the risk of selecting corrupted measurements. READ MORE
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5. Low Rank Matrix Factorization and Relative Pose Problems in Computer Vision
Abstract : This thesis is focused on geometric computer vision problems. The first part of the thesis aims at solving one fundamental problem, namely low-rank matrix factorization. We provide several novel insights into the problem. In brief, we characterize, generate, parametrize and solve the minimal problems associated with low-rank matrix factorization. READ MORE