情绪从何而来?预测情绪刺激图

Kuan-Chuan Peng, Amir Sadovnik, Andrew C. Gallagher, Tsuhan Chen
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引用次数: 63

摘要

图像的哪些部分能唤起观察者的情感?为了回答这个问题,我们在计算机视觉中引入了一个新的问题——预测情绪刺激图(ESM),它描述了像素对诱发情绪的贡献。建立EmotionROI图像数据库作为预测ESM的基准,我们发现显著性和物体检测选择的区域不能正确预测引起情感的图像区域。虽然物体代表了唤起情感的重要区域,但背景的某些部分也很重要。基于这一事实,我们建议使用全卷积网络来预测ESM。定性和定量实验结果都证实了我们的方法比显著性和客观检测更能预测引起情绪的区域。
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Where do emotions come from? Predicting the Emotion Stimuli Map
Which parts of an image evoke emotions in an observer? To answer this question, we introduce a novel problem in computer vision - predicting an Emotion Stimuli Map (ESM), which describes pixel-wise contribution to evoked emotions. Building a new image database, EmotionROI, as a benchmark for predicting the ESM, we find that the regions selected by saliency and objectness detection do not correctly predict the image regions which evoke emotion. Although objects represent important regions for evoking emotion, parts of the background are also important. Based on this fact, we propose using fully convolutional networks for predicting the ESM. Both qualitative and quantitative experimental results confirm that our method can predict the regions which evoke emotion better than both saliency and objectness detection.
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