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Head Pose Classification Based on Line Portrait

机译:基于线条肖像的头部姿势分类

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摘要

Head pose classification has great significance in the field of biometrics. But most of the head pose classification methods depend on facial landmark detection, which results in that the performance relies not only on the pose classification. To this end, this paper proposes a head pose classification method based on the algorithm of line portrait generation and convolutional neural network (CNN). Experiments on the Color FERET and BIWI database show that the proposed algorithm achieves better results than the algorithm of head pose classification depend on facial landmark detection and has strong robustness.
机译:头部姿势分类在生物识别领域具有重要意义。但是大多数头部姿势分类方法都依赖于面部界标检测,这导致性能不仅取决于姿势分类。为此,本文提出了一种基于线肖像生成和卷积神经网络(CNN)算法的头部姿势分类方法。在Color FERET和BIWI数据库上的实验表明,与基于面部标志检测的头部姿势分类算法相比,该算法取得了更好的效果,并且具有很强的鲁棒性。

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