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CBR Tagging of Emotions from Facial Expressions

机译:面部表情对情绪的CBR标记

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Mobility and context-awareness are two active research directions that open new potential to recommender systems. Usage of dynamically enriched information from the user context leads the system to find better solutions that are adapted to the specific situations. In this paper we focus on the difficult problem of dynamically acquiring the emotional context about the user during a recommendation process. We use the fact that emotions are tightly connected with facial expressions and it is difficult for people to hide emotions in facial expressions. We describe PhotoMood, a CBR system that uses gestures to identify emotions in faces, and present preliminary experiments with MadridLive, a mobile and context aware recommender system for leisure activities in Madrid. In the experiments, the momentary emotion of a user is dynamically detected from pictures of the facial expression taken unobtrusively with the front facing camera of the mobile device.
机译:移动性和上下文感知是两个活跃的研究方向,为推荐系统打开了新的潜力。使用来自用户上下文的动态丰富信息会导致系统找到适合特定情况的更好解决方案。在本文中,我们关注于在推荐过程中动态获取有关用户的情感情境的难题。我们利用这样的事实,即情绪与面部表情紧密相关,人们很难将情绪隐藏在面部表情中。我们将介绍使用手势识别面孔情绪的CBR系统PhotoMood,并使用MadridLive(马德里移动休闲和情境感知推荐系统,用于马德里的休闲活动)进行初步实验。在实验中,从使用移动设备的前置摄像头毫不干扰地拍摄的面部表情图片中动态检测用户的瞬时情感。

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