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 predict...

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Bibliographic Details
Published in2016 IEEE International Conference on Image Processing (ICIP) pp. 614 - 618
Main Authors Kuan-Chuan Peng, Sadovnik, Amir, Gallagher, Andrew, Tsuhan Chen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2016
Subjects
Benchmark testing
Buildings
Computer vision
Emotion stimuli map
fully convolutional networks
Measurement
Semantics
Training
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Summary: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.
ISSN:2381-8549
DOI:10.1109/ICIP.2016.7532430