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Emotion Recognition Using Feature-level Fusion of Facial Expressions and Body Gestures

机译:使用面部表情和手势的特征级融合的情绪识别

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Automatic emotion recognition using computer vision is significant for many real-world applications like photojournalism, virtual reality, sign language recognition, and Human Robot Interaction (HRI) etc., Psychological research findings advocate that humans depend on the collective visual conduits of face and body to comprehend human emotional behaviour. Plethora of studies have been done to analyse human emotions using facial expressions, EEG signals and speech etc., Most of the work done was based on single modality. Our objective is to efficiently integrate emotions recognized from facial expressions and upper body pose of humans using images. Our work on bimodal emotion recognition provides the benefits of the accuracy of both the modalities.
机译:使用计算机视觉进行自动情感识别对于许多现实世界的应用来说非常重要,例如新闻摄影,虚拟现实,手语识别和人机交互(HRI)等。心理学研究发现,人类依赖于面部和身体的集体视觉通道理解人类的情感行为。已经进行了大量研究以使用面部表情,EEG信号和语音等来分析人的情绪。完成的大多数工作都是基于单一模式。我们的目标是使用图像有效整合从面部表情和人的上半身姿势识别出的情绪。我们在双峰情感识别方面的工作提供了两种模态准确性的好处。

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