21,416 research outputs found

    Fast and Accurate Algorithm for Eye Localization for Gaze Tracking in Low Resolution Images

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    Iris centre localization in low-resolution visible images is a challenging problem in computer vision community due to noise, shadows, occlusions, pose variations, eye blinks, etc. This paper proposes an efficient method for determining iris centre in low-resolution images in the visible spectrum. Even low-cost consumer-grade webcams can be used for gaze tracking without any additional hardware. A two-stage algorithm is proposed for iris centre localization. The proposed method uses geometrical characteristics of the eye. In the first stage, a fast convolution based approach is used for obtaining the coarse location of iris centre (IC). The IC location is further refined in the second stage using boundary tracing and ellipse fitting. The algorithm has been evaluated in public databases like BioID, Gi4E and is found to outperform the state of the art methods.Comment: 12 pages, 10 figures, IET Computer Vision, 201

    Collocating Interface Objects: Zooming into Maps

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    May, Dean and Barnard [10] used a theoretically based model to argue that objects in a wide range of interfaces should be collocated following screen changes such as a zoom-in to detail. Many existing online maps do not follow this principle, but move a clicked point to the centre of the subsequent display, leaving the user looking at an unrelated location. This paper presents three experiments showing that collocating the point clicked on a map so that the detailed location appears in the place previously occupied by the overview location makes the map easier to use, reducing eye movements and interaction duration. We discuss the benefit of basing design principles on theoretical models so that they can be applied to novel situations, and so designers can infer when to use and not use them
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