{"title":"识别带有“快乐”或“悲伤”情绪的体育视频镜头","authors":"Jinjun Wang, Chng Eng Siong, Changsheng Xu, Hanqing Lu, Xiaofeng Tong","doi":"10.1109/ICME.2006.262641","DOIUrl":null,"url":null,"abstract":"Semantic video content extraction and selection are critical steps in sports video analysis and editing. The identification of video segments can be from various semantic perspectives, e.g. certain event, player or emotional state. In this paper, we examined the possibility of automatically identifying shots with \"happy\" or \"sad\" emotion from broadcast sports video. Our proposed model first performs the sports highlight extraction to obtain candidate shots that possibly contain emotion information and then classifies these shots into either \"happy\" or \"sad\" emotion groups using hidden Markov model based method. The final experimental results are satisfactory","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Identify Sports Video Shots with \\\"Happy\\\" or \\\"Sad\\\" Emotions\",\"authors\":\"Jinjun Wang, Chng Eng Siong, Changsheng Xu, Hanqing Lu, Xiaofeng Tong\",\"doi\":\"10.1109/ICME.2006.262641\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Semantic video content extraction and selection are critical steps in sports video analysis and editing. The identification of video segments can be from various semantic perspectives, e.g. certain event, player or emotional state. In this paper, we examined the possibility of automatically identifying shots with \\\"happy\\\" or \\\"sad\\\" emotion from broadcast sports video. Our proposed model first performs the sports highlight extraction to obtain candidate shots that possibly contain emotion information and then classifies these shots into either \\\"happy\\\" or \\\"sad\\\" emotion groups using hidden Markov model based method. The final experimental results are satisfactory\",\"PeriodicalId\":339258,\"journal\":{\"name\":\"2006 IEEE International Conference on Multimedia and Expo\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE International Conference on Multimedia and Expo\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICME.2006.262641\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE International Conference on Multimedia and Expo","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICME.2006.262641","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identify Sports Video Shots with "Happy" or "Sad" Emotions
Semantic video content extraction and selection are critical steps in sports video analysis and editing. The identification of video segments can be from various semantic perspectives, e.g. certain event, player or emotional state. In this paper, we examined the possibility of automatically identifying shots with "happy" or "sad" emotion from broadcast sports video. Our proposed model first performs the sports highlight extraction to obtain candidate shots that possibly contain emotion information and then classifies these shots into either "happy" or "sad" emotion groups using hidden Markov model based method. The final experimental results are satisfactory
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