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Robust face model based approach to head pose estimation

机译:基于鲁棒人脸模型的头部姿态估计方法

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摘要

Head pose estimation from camera images is a computational problem that may influence many sociological, cognitive, interaction and marketing researches. It is especially crucial in the process of visual gaze estimation which accuracy depends not only on eye region analysis, but head inferring as well. Presented method exploits a 3d head model for a user head pose estimation as it outperforms, in the context of performance, popular appearance based approaches and assures efficient face head pose analysis. The novelty of the presented approach lies in a default head model refinement according to the selected facial features localisation. The new method not only achieves very high precision (about 4°), but iteratively improves the reference head model. The results of the head pose inferring experiments were verified with professional Vicon motion tracking system and head model refinement accuracy was verified with high precision Artec structural light scanner.
机译:从摄像机图像估计头部姿势是一个计算问题,可能会影响许多社会学,认知,互动和市场研究。在视觉注视估计过程中,准确度不仅取决于眼睛区域分析,而且还取决于头部推断,这一点尤其重要。所提出的方法利用3d头部模型进行用户头部姿势估计,因为它在性能方面优于基于性能的流行外观方法,并确保有效的面部头部姿势分析。所提出的方法的新颖性在于根据所选面部特征定位的默认头部模型细化。新方法不仅实现了非常高的精度(大约4°),而且还迭代地改进了参考头模型。使用专业的Vicon运动跟踪系统验证了头部姿势推断实验的结果,并使用高精度的Artec结构光扫描仪验证了头部模型的精化精度。

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