{"title":"AIDanceFriend:一款使用人工智能和计算机视觉自动评分的智能移动应用程序","authors":"Yuanyuan Ding, Shuyu Wang","doi":"10.5121/csit.2023.130505","DOIUrl":null,"url":null,"abstract":"In recent years, dance has become a popular entertainment for many people and also an occupation. As a dancer, sometimes it is hard to check how close your cover is vs. the choreographer's because our eyes are not always accurate when we are judging dynamic movement of people, so can artificial intelligence help us to do the work? This paper develops an application which utilizes artificial intelligence, and data analysis skills to develop an application which works on dance scoring [4]. In the application, users can upload two videos, one is their own cover while another one is the original choreography. Then, the application will use MediaPipe to catch the angles of dancers’ bodies in frames then store them in a data abstraction [5]. After all data are collected, the application will use clustering to line up the frames and angles information that are stored. The steps above will be applied to both videos. Next, the application will use an algorithm to compare two videos’ data and calculate a percentage of error of the covering video to the original choreograph and report a grade to the user. We applied our application to users who want to check how similar their covering dances are compared to the original choreographs in order to improve their covering quality [6]. The results show that when users are improving the quality of their covers, they improve their skills of focusing and optimizing details in dance.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"143 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AIDanceFriend: An Intelligent Mobile Application to Automate the Dance Rating using Artificial Intelligence and Computer Vision\",\"authors\":\"Yuanyuan Ding, Shuyu Wang\",\"doi\":\"10.5121/csit.2023.130505\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, dance has become a popular entertainment for many people and also an occupation. As a dancer, sometimes it is hard to check how close your cover is vs. the choreographer's because our eyes are not always accurate when we are judging dynamic movement of people, so can artificial intelligence help us to do the work? This paper develops an application which utilizes artificial intelligence, and data analysis skills to develop an application which works on dance scoring [4]. In the application, users can upload two videos, one is their own cover while another one is the original choreography. Then, the application will use MediaPipe to catch the angles of dancers’ bodies in frames then store them in a data abstraction [5]. After all data are collected, the application will use clustering to line up the frames and angles information that are stored. The steps above will be applied to both videos. Next, the application will use an algorithm to compare two videos’ data and calculate a percentage of error of the covering video to the original choreograph and report a grade to the user. We applied our application to users who want to check how similar their covering dances are compared to the original choreographs in order to improve their covering quality [6]. The results show that when users are improving the quality of their covers, they improve their skills of focusing and optimizing details in dance.\",\"PeriodicalId\":261978,\"journal\":{\"name\":\"Computer Science, Engineering and Applications\",\"volume\":\"143 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Science, Engineering and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/csit.2023.130505\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Science, Engineering and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/csit.2023.130505","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AIDanceFriend: An Intelligent Mobile Application to Automate the Dance Rating using Artificial Intelligence and Computer Vision
In recent years, dance has become a popular entertainment for many people and also an occupation. As a dancer, sometimes it is hard to check how close your cover is vs. the choreographer's because our eyes are not always accurate when we are judging dynamic movement of people, so can artificial intelligence help us to do the work? This paper develops an application which utilizes artificial intelligence, and data analysis skills to develop an application which works on dance scoring [4]. In the application, users can upload two videos, one is their own cover while another one is the original choreography. Then, the application will use MediaPipe to catch the angles of dancers’ bodies in frames then store them in a data abstraction [5]. After all data are collected, the application will use clustering to line up the frames and angles information that are stored. The steps above will be applied to both videos. Next, the application will use an algorithm to compare two videos’ data and calculate a percentage of error of the covering video to the original choreograph and report a grade to the user. We applied our application to users who want to check how similar their covering dances are compared to the original choreographs in order to improve their covering quality [6]. The results show that when users are improving the quality of their covers, they improve their skills of focusing and optimizing details in dance.