论文标题
从面部表情自动检测感性
Automatic Detection of Sentimentality from Facial Expressions
论文作者
论文摘要
在过去的20年中，情感认可受到了计算机视觉社区的广泛关注。但是，大多数研究都侧重于分析六种基本情绪（例如，喜悦，愤怒，惊喜），有限地针对其他情感状态。在本文中，我们解决了一种感性（强烈的令人心动或怀旧的感觉），这是一种新的情绪状态，在文献中几乎没有作品，也没有定义其面部标记的指南。为此，我们首先收集了一个4.9k视频的数据集，该视频的参与者观看了一些感性和非情感广告，然后我们标记了广告中唤起情感的时刻。其次，我们使用不同框架上的AD级标签和面部动作单元（AUS）激活来定义一些弱框架级感性标签。第三，我们使用AUS激活来训练多层感知器（MLP）以进行感性检测。最后，我们定义了两个新的广告级指标，以评估我们的模型性能。定量和定性结果显示了感性检测的有希望的结果。据我们所知，这是解决感性检测问题的第一项工作。
Emotion recognition has received considerable attention from the Computer Vision community in the last 20 years. However, most of the research focused on analyzing the six basic emotions (e.g. joy, anger, surprise), with a limited work directed to other affective states. In this paper, we tackle sentimentality (strong feeling of heartwarming or nostalgia), a new emotional state that has few works in the literature, and no guideline defining its facial markers. To this end, we first collect a dataset of 4.9K videos of participants watching some sentimental and non-sentimental ads, and then we label the moments evoking sentimentality in the ads. Second, we use the ad-level labels and the facial Action Units (AUs) activation across different frames for defining some weak frame-level sentimentality labels. Third, we train a Multilayer Perceptron (MLP) using the AUs activation for sentimentality detection. Finally, we define two new ad-level metrics for evaluating our model performance. Quantitative and qualitative results show promising results for sentimentality detection. To the best of our knowledge this is the first work to address the problem of sentimentality detection.
