姿势导向关卡设计

Yongqi Zhang, Biao Xie, Haikun Huang, Elisa F. Ogawa, T. You, L. Yu
{"title":"姿势导向关卡设计","authors":"Yongqi Zhang, Biao Xie, Haikun Huang, Elisa F. Ogawa, T. You, L. Yu","doi":"10.1145/3290605.3300784","DOIUrl":null,"url":null,"abstract":"Player's physical experience is a critical factor to consider in designing motion-based games that are played through motion sensor gaming consoles or virtual reality devices. However, adjusting the physical challenge involved in a motion-based game is difficult and tedious, as it is typically done manually by level designers on a trial-and-error basis. In this paper, we propose a novel approach for automatically synthesizing levels for motion-based games that can achieve desired physical movement goals. By formulating the level design problem as a trans-dimensional optimization problem which is solved by a reversible-jump Markov chain Monte Carlo technique, we show that our approach can automatically synthesize a variety of game levels, each carrying the desired physical movement properties. To demonstrate the generality of our approach, we synthesize game levels for two different types of motion-based games and conduct a user study to validate the effectiveness of our approach.","PeriodicalId":20454,"journal":{"name":"Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Pose-Guided Level Design\",\"authors\":\"Yongqi Zhang, Biao Xie, Haikun Huang, Elisa F. Ogawa, T. You, L. Yu\",\"doi\":\"10.1145/3290605.3300784\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Player's physical experience is a critical factor to consider in designing motion-based games that are played through motion sensor gaming consoles or virtual reality devices. However, adjusting the physical challenge involved in a motion-based game is difficult and tedious, as it is typically done manually by level designers on a trial-and-error basis. In this paper, we propose a novel approach for automatically synthesizing levels for motion-based games that can achieve desired physical movement goals. By formulating the level design problem as a trans-dimensional optimization problem which is solved by a reversible-jump Markov chain Monte Carlo technique, we show that our approach can automatically synthesize a variety of game levels, each carrying the desired physical movement properties. To demonstrate the generality of our approach, we synthesize game levels for two different types of motion-based games and conduct a user study to validate the effectiveness of our approach.\",\"PeriodicalId\":20454,\"journal\":{\"name\":\"Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3290605.3300784\",\"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 2019 CHI Conference on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3290605.3300784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

在设计通过动作传感器游戏机或虚拟现实设备玩的基于动作的游戏时,玩家的身体体验是考虑的关键因素。然而,调整基于动作的游戏中的物理挑战既困难又乏味,因为这通常是由关卡设计师在反复试验的基础上手动完成的。在本文中,我们提出了一种自动合成基于动作的游戏关卡的新方法,可以实现期望的物理运动目标。通过将关卡设计问题表述为一个跨维优化问题,并通过可逆跳跃马尔可夫链蒙特卡罗技术来解决,我们表明我们的方法可以自动合成各种游戏关卡,每个关卡都带有所需的物理运动属性。为了证明我们方法的普遍性,我们综合了两种不同类型的基于动作的游戏的游戏关卡,并进行了用户研究来验证我们方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pose-Guided Level Design
Player's physical experience is a critical factor to consider in designing motion-based games that are played through motion sensor gaming consoles or virtual reality devices. However, adjusting the physical challenge involved in a motion-based game is difficult and tedious, as it is typically done manually by level designers on a trial-and-error basis. In this paper, we propose a novel approach for automatically synthesizing levels for motion-based games that can achieve desired physical movement goals. By formulating the level design problem as a trans-dimensional optimization problem which is solved by a reversible-jump Markov chain Monte Carlo technique, we show that our approach can automatically synthesize a variety of game levels, each carrying the desired physical movement properties. To demonstrate the generality of our approach, we synthesize game levels for two different types of motion-based games and conduct a user study to validate the effectiveness of our approach.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信