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Dealing with Inaccurate Face Detection for Automatic Gender Recognition with Partially Occluded Faces

机译:处理不正确的面部检测以部分遮挡的面部自动识别性别

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Gender recognition problem has not been extensively studied in situations where the face cannot be accurately detected and it also can be partially occluded. In this contribution, a comparison of several characterisation methods of the face is presented and they are evaluated in four different experiments that simulate the previous scenario. Two of the characterisation techniques are based on histograms, LBP and local contrast values, and the other one is a new kind of features, called Ranking Labels, that provide spatial information. Experiments have proved Ranking Labels description is the most reliable in inaccurate situations.
机译:在无法准确检测面部并且也可能部分遮挡面部的情况下,尚未广泛研究性别识别问题。在此贡献中,介绍了面部的几种表征方法的比较,并在模拟先前场景的四个不同实验中对它们进行了评估。两种表征技术基于直方图,LBP和局部对比度值,另一种表征是一种新的功能,称为排名标签,可提供空间信息。实验证明,在不准确的情况下,“排名标签”描述是最可靠的。

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