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- W2019946986 abstract "This paper presents a method for the detection of faces (via skin regions) in images where faces may be low-resolution and noassumptions are made about fine facial features being visible. This type of data is challenging because changes in appearanceof skin regions occur due to changes in both lighting and resolution. We present a non-parametric classification scheme basedon a histogram similarity measure. By comparing performance of commonly-used colour-spaces we find that the YIQ colourspace with 16 histogram bins (in both 1 and 2 dimensions) gives the most accurate performance over a wide range of imagingconditions for non-parametric skin classification. We demonstrate better performance of the non-parametric approach vs.colour thresholding and a Gaussian classifier. Face detection is subsequently achieved via a simple aspect-ratio and we showresults from indoor and outdoor scenes." @default.
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- W2019946986 date "2009-01-18" @default.
- W2019946986 modified "2023-09-23" @default.
- W2019946986 title "Detecting low-resolution faces in video" @default.
- W2019946986 doi "https://doi.org/10.1117/12.805984" @default.
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