We describe our approach towards building an efficient predictive model to detect emotions for a group of people in an image. We have proposed that training a Convolutional Neural Network (CNN) model on the emotion heatmaps extracted from the image, outperforms a CNN model trained entirely on the raw images. The comparison of the models have been done on a recently published dataset of Emotion Recognition in theWild (EmotiW) challenge, 2017. The proposed method 1 achieved validation accuracy of 55.23% which is 2.44% above the baseline accuracy, provided by the EmotiW organizers.
{"title":"Group Affect Prediction Using Multimodal Distributions","authors":"Saqib Nizam Shamsi, Bhanu Pratap Singh, Manya Wadhwa","doi":"10.1109/WACVW.2018.00015","DOIUrl":"https://doi.org/10.1109/WACVW.2018.00015","url":null,"abstract":"We describe our approach towards building an efficient predictive model to detect emotions for a group of people in an image. We have proposed that training a Convolutional Neural Network (CNN) model on the emotion heatmaps extracted from the image, outperforms a CNN model trained entirely on the raw images. The comparison of the models have been done on a recently published dataset of Emotion Recognition in theWild (EmotiW) challenge, 2017. The proposed method 1 achieved validation accuracy of 55.23% which is 2.44% above the baseline accuracy, provided by the EmotiW organizers.","PeriodicalId":301220,"journal":{"name":"2018 IEEE Winter Applications of Computer Vision Workshops (WACVW)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123227728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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