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FACIAL FEATURE TRACKING COMBINING MODEL-BASED AND MODEL-FREE METHOD

机译:面部特征跟踪组合模型基于模型和模型方法

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In this paper we propose a novel facial feature tracker, which integrates model-free and model-based method to reliably track dense facial features with complex non-rigid motions in low quality video sequence. The tracker consists the mouth motion model part and the enhanced KLT tracker part. There are three key elements in our algorithms: dense facial feature tracking, noise removal with global rank constraints and characteristic non-rigid motion description. Experiments show good results on tracking dense facial features under various expressions, even some facial features have degenerate features.
机译:在本文中,我们提出了一种新颖的面部特征跟踪器,它集成了无模型和基于模型的方法,以可靠地跟踪密集的面部特征,以低质量的视频序列复杂的非刚性运动。跟踪器由口腔运动模型部分和增强型KLT跟踪器部件组成。我们的算法中有三个关键元素:密集的面部特征跟踪,噪声去除,具有全局秩约束和特征非刚性运动描述。实验表明,在各种表情下跟踪密集面部特征的良好结果,即使某些面部特征也具有堕落的功能。

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