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    • 53. 发明授权
    • Estimating facial pose from a sparse representation
    • 从稀疏表示估计面部姿势
    • US07526123B2
    • 2009-04-28
    • US10813767
    • 2004-03-31
    • Hankyu MoonMatthew L. Miller
    • Hankyu MoonMatthew L. Miller
    • G06K9/62
    • G06K9/00248
    • A method for accurately estimating a pose of the human head in natural scenes utilizing positions of the prominent facial features relative to the position of the head. A high-dimensional, randomly sparse representation of a human face, using a simplified facial feature model transforms a raw face image into sets of vectors representing the fits of the face to a random, sparse set of model configurations. The transformation collects salient features of the face image which are useful to estimate the pose, while suppressing irrelevant variations of face appearance. The relation between the sparse representation of the pose is learned using Support Vector Regression (SVR). The sparse representation, combined with the SVR learning is then used to estimate a pose of facial images.
    • 一种用于使用相对于头部的位置的显着面部特征的位置来精确估计自然场景中人头姿势的方法。 使用简化的面部特征模型,人脸的高维随机稀疏表示将原始脸部图像转换为表示脸部拟合到向量模型配置的随机,稀疏集合的向量集合。 该变换收集了面部图像的显着特征,这对于估计姿势是有用的,同时抑制了脸部外观的不相关变化。 使用支持向量回归(SVR)学习姿势的稀疏表示之间的关系。 然后将稀疏表示结合SVR学习用于估计面部图像的姿态。