文件名称:Face-detection-algorhitms
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Abstract— When skin areas like faces and hands are imaged under natural environments their color appearance is frequently
affected by variations in illumination intensity and chromaticity. In color-based skin tracking and detection, changing
intensity is often dismissed either with the use of normalized, intensity-invariant color coordinates or by additionally modeling
possible skin intensities. Chromaticity variations are rarely considered although they are common in practice. In most
approaches considering chromaticity the experiments are done with a small or undefined variation range. It is difficult to
compare different approaches and assess their applicability range for this reason. To improve the situation, we evaluate the
performance of four state-of-the-art methods under drastic but practically common illumination changes. The effect of
illumination chromaticity for skin is clearly defined, and based on it we draw conclusion about the performance of these
approaches.
affected by variations in illumination intensity and chromaticity. In color-based skin tracking and detection, changing
intensity is often dismissed either with the use of normalized, intensity-invariant color coordinates or by additionally modeling
possible skin intensities. Chromaticity variations are rarely considered although they are common in practice. In most
approaches considering chromaticity the experiments are done with a small or undefined variation range. It is difficult to
compare different approaches and assess their applicability range for this reason. To improve the situation, we evaluate the
performance of four state-of-the-art methods under drastic but practically common illumination changes. The effect of
illumination chromaticity for skin is clearly defined, and based on it we draw conclusion about the performance of these
approaches.
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