{"title":"小鼠对第一人称目标任务的敏感性","authors":"Ben Boudaoud;Josef Spjut;Joohwan Kim","doi":"10.1109/TG.2023.3293692","DOIUrl":null,"url":null,"abstract":"Mouse sensitivity in first-person targeting tasks is a highly debated issue. Recommendations within a single game can vary by a factor of 10× or more and are an active topic of experimentation in both competitive and recreational esports communities. Inspired by work in pointer-based gain optimization and extending our previous results from the first user study focused on mouse sensitivity in first-person targeting tasks (Boudaoud et al., 2023), we describe a range of optimal mouse sensitivity wherein players perform statistically significantly better in task completion time and throughput. For tasks involving first-person view control, mouse sensitivity is best described using the ratio between an in-game rotation of the view and corresponding physical displacement of the mouse. We discuss how this displacement-to-rotation sensitivity is incompatible with the control-display gain reported in traditional pointer-based gain studies as well as other rotational gains reported in head-controlled interface studies. We provide additional details regarding impacts of mouse dots per inch, on reported sensitivity, the distribution of spatial difficulty in our experiment, our submovement parsing algorithm, and relationships between measured parameters, further demonstrating optimal sensitivity arising from a speed-precision tradeoff. We conclude our work by updating and improving our suggestions for mouse sensitivity selection and refining directions for future work.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"15 4","pages":"493-506"},"PeriodicalIF":1.7000,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mouse Sensitivity in First-Person Targeting Tasks\",\"authors\":\"Ben Boudaoud;Josef Spjut;Joohwan Kim\",\"doi\":\"10.1109/TG.2023.3293692\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mouse sensitivity in first-person targeting tasks is a highly debated issue. Recommendations within a single game can vary by a factor of 10× or more and are an active topic of experimentation in both competitive and recreational esports communities. Inspired by work in pointer-based gain optimization and extending our previous results from the first user study focused on mouse sensitivity in first-person targeting tasks (Boudaoud et al., 2023), we describe a range of optimal mouse sensitivity wherein players perform statistically significantly better in task completion time and throughput. For tasks involving first-person view control, mouse sensitivity is best described using the ratio between an in-game rotation of the view and corresponding physical displacement of the mouse. We discuss how this displacement-to-rotation sensitivity is incompatible with the control-display gain reported in traditional pointer-based gain studies as well as other rotational gains reported in head-controlled interface studies. We provide additional details regarding impacts of mouse dots per inch, on reported sensitivity, the distribution of spatial difficulty in our experiment, our submovement parsing algorithm, and relationships between measured parameters, further demonstrating optimal sensitivity arising from a speed-precision tradeoff. We conclude our work by updating and improving our suggestions for mouse sensitivity selection and refining directions for future work.\",\"PeriodicalId\":55977,\"journal\":{\"name\":\"IEEE Transactions on Games\",\"volume\":\"15 4\",\"pages\":\"493-506\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Games\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10184504/\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Games","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10184504/","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
摘要
第一人称目标任务中的鼠标敏感度是一个备受争议的问题。单个游戏中的推荐可能会有10倍甚至更多的差异,这在竞技和娱乐电子竞技社区中都是一个活跃的实验主题。受基于指针的增益优化工作的启发,并扩展了我们之前关于第一人称目标任务中鼠标灵敏度的第一项用户研究的结果(Boudaoud et al., 2023),我们描述了一系列最佳鼠标灵敏度,其中玩家在任务完成时间和吞吐量方面的表现在统计上明显更好。对于涉及第一人称视角控制的任务,鼠标灵敏度最好用游戏内视角旋转与鼠标相应物理位移之间的比率来描述。我们讨论了这种位移-旋转灵敏度如何与传统的基于指针的增益研究中报告的控制-显示增益以及头控界面研究中报告的其他旋转增益不兼容。我们提供了关于每英寸鼠标点对报告灵敏度的影响、实验中空间难度的分布、子运动解析算法以及测量参数之间关系的额外细节,进一步展示了速度-精度权衡产生的最佳灵敏度。最后,我们对鼠标灵敏度选择的建议进行了更新和完善,并为今后的工作指明了方向。
Mouse sensitivity in first-person targeting tasks is a highly debated issue. Recommendations within a single game can vary by a factor of 10× or more and are an active topic of experimentation in both competitive and recreational esports communities. Inspired by work in pointer-based gain optimization and extending our previous results from the first user study focused on mouse sensitivity in first-person targeting tasks (Boudaoud et al., 2023), we describe a range of optimal mouse sensitivity wherein players perform statistically significantly better in task completion time and throughput. For tasks involving first-person view control, mouse sensitivity is best described using the ratio between an in-game rotation of the view and corresponding physical displacement of the mouse. We discuss how this displacement-to-rotation sensitivity is incompatible with the control-display gain reported in traditional pointer-based gain studies as well as other rotational gains reported in head-controlled interface studies. We provide additional details regarding impacts of mouse dots per inch, on reported sensitivity, the distribution of spatial difficulty in our experiment, our submovement parsing algorithm, and relationships between measured parameters, further demonstrating optimal sensitivity arising from a speed-precision tradeoff. We conclude our work by updating and improving our suggestions for mouse sensitivity selection and refining directions for future work.