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Analyzing the Effect of Eye Center Localization on Accurate Landmark Localization in a Facial Image

机译:分析人眼中心定位对面部图像中精确地标定位的影响

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Localization of facial landmarks on a human face is an important step for many face-related computer vision applications. The most of the earlier techniques (AAMs, CLMs) has achieved good performance in landmark localization but they always limited by the initialization of landmarks. In this paper, the initialization problem is solved by taking the eye center as references to the mean face shape. In the proposed method, the eye centers are estimated using multi-scale iris shape feature first and then the constrained local model is applied for landmark localization where initialization is done using mean face shape taking eye centers as references. The performance of eye center estimation and landmark localization method are evaluated on AR and Multi-PIE databases. For eye center estimation three normalized eye localization error is considered whereas for landmark localization RMSE and detection rate are considered. For landmark localization, a total of 130 and 68 landmarks are considered for AR and Multi-PIE database respectively. The experimental results suggest that the proposed method has achieved improved performance as compared to some of the other methods.
机译:对于许多与面部相关的计算机视觉应用,人脸上的面部标志的本地化是重要的一步。大多数较早的技术(AAM,CLM)在地标定位中均取得了良好的性能,但它们始终受地标初始化的限制。在本文中,初始化问题是通过将眼睛中心作为参考平均脸部形状来解决的。在提出的方法中,首先使用多尺度虹膜形状特征估计眼睛中心,然后将受约束的局部模型应用于界标定位,其中使用以眼睛中心为参考的平均脸部形状进行初始化。在AR和Multi-PIE数据库上评估了眼中心估计和界标定位方法的性能。对于眼中心估计,考虑了三个标准化的眼定位误差,而对于界标定位,则考虑了RMSE和检测率。对于地标定位,AR和Multi-PIE数据库分别考虑了130和68个地标。实验结果表明,与其他方法相比,该方法具有更高的性能。

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