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Low Resolution Sparse Binary Face Patterns
<span title="">2016</span>
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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tyl5kfigejfehnouax7r3tii24" style="color: black;">Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications</a>
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Automated recognition of low resolution face images from thumbnails represent a challenging image recognition problem. We propose the sequential fusion of wavelet transform computation, local binary pattern and sparse coding of images to accurately extract facial features from thumbnail images. A minimum distance classifier with Shepard's similarity measure is used as the classifier. The proposed method shows robust recognition performance when tested on face datasets (Yale B, AR and PUT) when
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... ompared against benchmark techniques for very low resolution (i.e. less than 45x45 pixels) face image recognition. The possible applications of the proposed thumbnail recognition include contextual search, intelligent image/video sorting and groups, and face image clustering.
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