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Cognitive Behaviour Analysis Based on Facial Information Using Depth Sensors

机译:深度传感器基于面部信息的认知行为分析

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Cognitive behaviour analysis is considered of high importance with many innovative applications in a range of sectors including healthcare, education, robotics and entertainment. In healthcare, cognitive and emotional behaviour analysis helps to improve the quality of life of patients and their families. Amongst all the different approaches for cognitive behaviour analysis, significant work has been focused on emotion analysis through facial expressions using depth and EEG data. Our work introduces an emotion recognition approach using facial expressions based on depth data and landmarks. A novel dataset was created that triggers emotions from long or short term memories. This work uses novel features based on a non-linear dimensionality reduction, t-SNE, applied on facial landmarks and depth data. Its performance was evaluated in a comparative study, proving that our approach outperforms other state-of-the-art features.
机译:认知行为分析在医疗,教育,机器人和娱乐等众多领域的许多创新应用中被认为具有高度重要性。在医疗保健中,认知和情绪行为分析有助于改善患者及其家人的生活质量。在认知行为分析的所有不同方法中,重要的工作已集中在通过使用深度和EEG数据的面部表情进行情绪分析。我们的工作引入了一种基于深度数据和界标的面部表情情感识别方法。创建了一个新颖的数据集,该数据集触发了长期或短期记忆中的情绪。这项工作使用了基于非线性降维t-SNE的新颖功能,应用于面部标志和深度数据。在一项比较研究中对它的性能进行了评估,证明了我们的方法优于其他最新功能。

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