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    • 44. 发明授权
    • Face recognition system
    • 人脸识别系统
    • US07430315B2
    • 2008-09-30
    • US10858930
    • 2004-06-01
    • Ming-Hsuan YangJongwoo LimDavid RossTakahiro Ohashi
    • Ming-Hsuan YangJongwoo LimDavid RossTakahiro Ohashi
    • G06K9/62G06K9/64G06K9/40
    • G06K9/6269G06K9/00228G06K9/6857
    • The face detection system and method attempts classification of a test image before performing all of the kernel evaluations. Many subimages are not faces and should be relatively easy to identify as such. Thus, the SVM classifier try to discard non-face images using as few kernel evaluations as possible using a cascade SVM classification. In the first stage, a score is computed for the first two support vectors, and the score is compared to a threshold. If the score is below the threshold value, the subimage is classified as not a face. If the score is above the threshold value, the cascade SVM classification function continues to apply more complicated decision rules, each time doubling the number of kernel evaluations, classifying the image as a non-face (and thus terminating the process) as soon as the test image fails to satisfy one of the decision rules. Finally, if the subimage has satisfied all intermediary decision rules, and has now reached the point at which all support vectors must be considered, the original decision function is applied. Satisfying this final rule, and all intermediary rules, is the only way for a test image to garner a positive (face) classification.
    • 面部检测系统和方法在执行所有内核评估之前尝试对测试图像进​​行分类。 许多子图像不是面孔,应该比较容易识别。 因此,SVM分类器尝试使用级联SVM分类使用尽可能少的内核评估来丢弃非面部图像。 在第一阶段,对前两个支持向量计算分数,并将分数与阈值进行比较。 如果分数低于阈值,则子图像被分类为不是脸部。 如果分数高于阈值,则级联SVM分类功能继续应用更复杂的决策规则,每次将内核评估的数量加倍,将图像分类为非面(并因此终止进程),一旦 测试图像不能满足其中一个决策规则。 最后,如果子图像满足了所有的中介决策规则,并且现在已经到了必须考虑所有支持向量的点,则应用原始决策函数。 满足这个最终规则和所有中介规则是测试图像获得积极(面部)分类的唯一方法。