{"title":"基于视听分析的游戏性能分割的后处理游戏参数","authors":"Raphaël Marczak, G. Schott, P. Hanna","doi":"10.1109/TCIAIG.2014.2382718","DOIUrl":null,"url":null,"abstract":"This paper introduces a new variant of gameplay metrics that further develops a set of processes that expand user-centered game testing practices capable of quantifying user experiences. The key goal of the method presented here is to widen the appeal and application of game metrics within research relevant to, and representative of the wider field of game studies. In doing so, we acknowledge that the interests of this research community is often focused on player experience and performance with a broad range of off-the-shelf games that have already been released to the public. In order to be able to include any PC game system within research (or audiovideo stream, e.g., YouTube walkthroughs) our approach comprises of a postprocessing method for analyzing player performance. Through exploiting the audiovisual streams that are transmitted to the player, this approach processes content activated and generated during play and is therefore representative of individual player's encounters with specific games.","PeriodicalId":49192,"journal":{"name":"IEEE Transactions on Computational Intelligence and AI in Games","volume":"7 1","pages":"279-291"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TCIAIG.2014.2382718","citationCount":"6","resultStr":"{\"title\":\"Postprocessing Gameplay Metrics for Gameplay Performance Segmentation Based on Audiovisual Analysis\",\"authors\":\"Raphaël Marczak, G. Schott, P. Hanna\",\"doi\":\"10.1109/TCIAIG.2014.2382718\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a new variant of gameplay metrics that further develops a set of processes that expand user-centered game testing practices capable of quantifying user experiences. The key goal of the method presented here is to widen the appeal and application of game metrics within research relevant to, and representative of the wider field of game studies. In doing so, we acknowledge that the interests of this research community is often focused on player experience and performance with a broad range of off-the-shelf games that have already been released to the public. In order to be able to include any PC game system within research (or audiovideo stream, e.g., YouTube walkthroughs) our approach comprises of a postprocessing method for analyzing player performance. Through exploiting the audiovisual streams that are transmitted to the player, this approach processes content activated and generated during play and is therefore representative of individual player's encounters with specific games.\",\"PeriodicalId\":49192,\"journal\":{\"name\":\"IEEE Transactions on Computational Intelligence and AI in Games\",\"volume\":\"7 1\",\"pages\":\"279-291\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/TCIAIG.2014.2382718\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Computational Intelligence and AI in Games\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TCIAIG.2014.2382718\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Intelligence and AI in Games","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TCIAIG.2014.2382718","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Computer Science","Score":null,"Total":0}
Postprocessing Gameplay Metrics for Gameplay Performance Segmentation Based on Audiovisual Analysis
This paper introduces a new variant of gameplay metrics that further develops a set of processes that expand user-centered game testing practices capable of quantifying user experiences. The key goal of the method presented here is to widen the appeal and application of game metrics within research relevant to, and representative of the wider field of game studies. In doing so, we acknowledge that the interests of this research community is often focused on player experience and performance with a broad range of off-the-shelf games that have already been released to the public. In order to be able to include any PC game system within research (or audiovideo stream, e.g., YouTube walkthroughs) our approach comprises of a postprocessing method for analyzing player performance. Through exploiting the audiovisual streams that are transmitted to the player, this approach processes content activated and generated during play and is therefore representative of individual player's encounters with specific games.
期刊介绍:
Cessation. The IEEE Transactions on Computational Intelligence and AI in Games (T-CIAIG) publishes archival journal quality original papers in computational intelligence and related areas in artificial intelligence applied to games, including but not limited to videogames, mathematical games, human–computer interactions in games, and games involving physical objects. Emphasis is placed on the use of these methods to improve performance in and understanding of the dynamics of games, as well as gaining insight into the properties of the methods as applied to games. It also includes using games as a platform for building intelligent embedded agents for the real world. Papers connecting games to all areas of computational intelligence and traditional AI are considered.