基于时间自相似性和面部标志词袋的面部表情和头部手势识别

Ismail Ari, Hua Gao, H. K. Ekenel, L. Akarun
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引用次数: 0

摘要

面部表情和头部动作的自动识别在手语识别和人机交互等广泛的研究领域中占有重要地位。在这项工作中,我们采用性能良好的基于自相似度的动作识别方法对面部表情和头部手势进行分类。此外,我们提出了一种基于跟踪面部标志直方图的面部手势识别新方法。我们将所提出的技术与之前基于隐马尔可夫模型的方法[1]融合在一起,分类结果提高了15%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Facial expression and head gesture recognition using temporal self-similarity and bag of words of facial landmarks
Automatic recognition of facial expressions and head gestures plays an important role in a wide range of research area including sign language recognition and human-computer interaction. In this work, we adopt the well-performing self-similarity based action recognition method to classify facial expressions and head gestures. Additionally, we propose a novel approach for facial gesture recognition based on the histogram of tracked facial landmarks. We fuse the presented techniques with our previous Hidden Markov Model based approach [1] and get 15% increase in classification results.
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