Abhinav Dhall, Roland Göcke, Jyoti Joshi, Karan Sikka, Tom Gedeon
{"title":"2014年野生挑战中的情感识别:基线,数据和协议","authors":"Abhinav Dhall, Roland Göcke, Jyoti Joshi, Karan Sikka, Tom Gedeon","doi":"10.1145/2663204.2666275","DOIUrl":null,"url":null,"abstract":"The Second Emotion Recognition In The Wild Challenge (EmotiW) 2014 consists of an audio-video based emotion classification challenge, which mimics the real-world conditions. Traditionally, emotion recognition has been performed on data captured in constrained lab-controlled like environment. While this data was a good starting point, such lab controlled data poorly represents the environment and conditions faced in real-world situations. With the exponential increase in the number of video clips being uploaded online, it is worthwhile to explore the performance of emotion recognition methods that work `in the wild'. The goal of this Grand Challenge is to carry forward the common platform defined during EmotiW 2013, for evaluation of emotion recognition methods in real-world conditions. The database in the 2014 challenge is the Acted Facial Expression In Wild (AFEW) 4.0, which has been collected from movies showing close-to-real-world conditions. The paper describes the data partitions, the baseline method and the experimental protocol.","PeriodicalId":389037,"journal":{"name":"Proceedings of the 16th International Conference on Multimodal Interaction","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"224","resultStr":"{\"title\":\"Emotion Recognition In The Wild Challenge 2014: Baseline, Data and Protocol\",\"authors\":\"Abhinav Dhall, Roland Göcke, Jyoti Joshi, Karan Sikka, Tom Gedeon\",\"doi\":\"10.1145/2663204.2666275\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Second Emotion Recognition In The Wild Challenge (EmotiW) 2014 consists of an audio-video based emotion classification challenge, which mimics the real-world conditions. Traditionally, emotion recognition has been performed on data captured in constrained lab-controlled like environment. While this data was a good starting point, such lab controlled data poorly represents the environment and conditions faced in real-world situations. With the exponential increase in the number of video clips being uploaded online, it is worthwhile to explore the performance of emotion recognition methods that work `in the wild'. The goal of this Grand Challenge is to carry forward the common platform defined during EmotiW 2013, for evaluation of emotion recognition methods in real-world conditions. The database in the 2014 challenge is the Acted Facial Expression In Wild (AFEW) 4.0, which has been collected from movies showing close-to-real-world conditions. The paper describes the data partitions, the baseline method and the experimental protocol.\",\"PeriodicalId\":389037,\"journal\":{\"name\":\"Proceedings of the 16th International Conference on Multimodal Interaction\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"224\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 16th International Conference on Multimodal Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2663204.2666275\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 16th International Conference on Multimodal Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2663204.2666275","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Emotion Recognition In The Wild Challenge 2014: Baseline, Data and Protocol
The Second Emotion Recognition In The Wild Challenge (EmotiW) 2014 consists of an audio-video based emotion classification challenge, which mimics the real-world conditions. Traditionally, emotion recognition has been performed on data captured in constrained lab-controlled like environment. While this data was a good starting point, such lab controlled data poorly represents the environment and conditions faced in real-world situations. With the exponential increase in the number of video clips being uploaded online, it is worthwhile to explore the performance of emotion recognition methods that work `in the wild'. The goal of this Grand Challenge is to carry forward the common platform defined during EmotiW 2013, for evaluation of emotion recognition methods in real-world conditions. The database in the 2014 challenge is the Acted Facial Expression In Wild (AFEW) 4.0, which has been collected from movies showing close-to-real-world conditions. The paper describes the data partitions, the baseline method and the experimental protocol.