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A robust real-time facial alignment system with facial landmarks detection and rectification for multimedia applications

机译：具有面部地标检测和多媒体应用整流的强大实时面部对准系统

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摘要

Face detection often plays the first step in various visual applications. Large variants of facial deformations due to head movements and facial expression make it difficult to identify appropriate face region. In this paper, a robust real-time face alignment system, including facial landmarks detection and face rectification, is proposed. A facial landmarks detection model based on regression tree is utilized in the proposed system. In face rectification framework, 2-D geometrical analysis based on pitch, yaw and roll movements is designed to solve the misalignment problem in face detection. The experiments on the two datasets verify the performance significantly improved by the proposed method in the facial recognition task and outperform than those obtained by other alignment methods. Furthermore, the proposed method can achieve robust recognition results even if the amount of training images is not large.
机译：面部检测通常在各种可视应用中播放第一步。 由于头部运动和面部表达引起的面部变形的大变型使得难以识别适当的面部区域。 在本文中，提出了一种坚固的实时面对准系统，包括面部地标检测和面部整流。 基于回归树的面部地标检测模型在提出的系统中使用。 在面部整流框架中，基于间距的2-D几何分析，横摆和滚动运动旨在解决面部检测中的未对准问题。 两个数据集的实验验证了面部识别任务中所提出的方法显着改善的性能，而不是通过其他对准方法获得的方法。 此外，所提出的方法即使训练图像的量不大，也可以实现鲁棒识别结果。

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