首页> 外文学位 >Directing Virtual Humans Using Play-Scripts and Spatio-Temporal Reasoning
【24h】

Directing Virtual Humans Using Play-Scripts and Spatio-Temporal Reasoning

机译:使用播放脚本和时空推理指导虚拟人

获取原文
获取原文并翻译 | 示例

摘要

Historically, most virtual human character research focuses on realism/emotions, interaction with humans, and discourse. The majority of the spatial positioning of characters has focused on one-on-one conversations with humans or placing virtual characters side-by-side when talking. These rely on conversation space as the main driver (if any) for character placement.;Movies and games rely on motion capture (mocap) files and hard-coded functions to perform spatial movements. These require extensive technical knowledge just to have a character move from one place to another. Other methods involve the use of Behavior Markup Language (BML), a form of XML, which describes character behaviors. BML Realizers take this BML and perform the requested behavior(s) on the character(s). Also, there are waypoint and other spatial navigation schemes, but they primarily focus on traversals and not correct positioning. Each of these require a fair amount of low-level detail and knowledge to write, plus BML realizers are still in their early stages of development.;Theatre, movies, and television all utilize a form of play-scripts, which provide detailed information on what the actor must do spatially, and when for a particular scene (that is spatio-temporal direction). These involve annotations, in addition to the speech, which identify scene setups, character movements, and entrances /exits. Humans have the ability to take these play-scripts and easily perform a believable scene.;This research focuses on utilizing play-scripts to provide spatio-temporal direction to virtual characters within a scene. Because of the simplicity of creating a playscript, and our algorithms to interpret the scripts, we are able to provide a quick method of blocking scenes with virtual characters.;We focus on not only an all-virtual cast of characters, but also human-controlled characters intermixing with the virtual characters for the scene. The key here is that human-controlled characters introduce a dynamic spatial component that affects how the virtual characters should perform the scene to ensure continuity, cohesion, and inclusion with the human-controlled character.;The algorithms to accomplish the blocking of a scene from a standard play-script are the core research contribution. These techniques include some part of speech tagging, named entity recognition, a rules engine, and strategically designed force-directed graphs. With these methods, we are able to similarly map any play-script's spatial positioning of characters to a human-performed version of the same playscript. Also, human-based evaluations indicate these methods provide a qualitatively good performance.;Potential applications include: a rehearsal tool for actors; a director tool to help create a play-script; a controller for virtual human characters in games or virtual environments; or a planning tool for positioning people in an industrial environment.
机译:从历史上看,大多数虚拟人格研究都集中在现实主义/情感,与人的互动以及话语上。角色的大部分空间定位都集中在与人进行一对一对话,或者在交谈时将虚拟角色并排放置。这些依赖于对话空间作为角色放置的主要驱动器(如果有)。电影和游戏依赖于运动捕捉(mocap)文件和硬编码功能来执行空间运动。这些要求广泛的技术知识,才能使角色从一个地方移到另一个地方。其他方法包括使用行为标记语言(BML)(一种描述字符行为的XML形式)的使用。 BML实现器采用此BML并在角色上执行请求的行为。此外,还有航点和其他空间导航方案,但它们主要侧重于遍历而不是正确的定位。其中每一个都需要大量的底层细节和知识来编写,此外BML实现者还处于开发的早期阶段。剧院,电影和电视都使用一种播放脚本的形式,这些脚本提供了有关以下内容的详细信息:演员必须在空间上做什么,以及何时针对特定场景(即时空方向)。除了语音以外,这些还涉及注释,这些注释标识场景设置,角色移动和入口/出口。人类有能力拍摄这些剧本并轻松地表现出可信的场景。本研究的重点是利用剧本为场景中的虚拟角色提供时空方向。由于创建剧本的简便性以及我们解释剧本的算法,我们能够提供一种快速的方法来屏蔽带有虚拟角色的场景。我们不仅关注角色的全虚拟演员,还关注人类控制角色与场景的虚拟角色混合在一起。这里的关键是人为控制的角色引入了动态空间分量,该分量会影响虚拟角色应如何执行场景以确保连续性,凝聚力和与人为控制的角色的包容性;实现从场景中阻挡场景的算法标准的剧本是核心研究成果。这些技术包括语音标记,命名实体识别,规则引擎和经过战略设计的力导向图的某些部分。使用这些方法,我们可以将任何剧本的角色空间定位类似地映射到同一剧本的人为执行版本。同样,基于人的评估表明这些方法在质量上具有良好的表现。潜在的应用包括:演员演练工具;导演工具,可帮助创建剧本;游戏或虚拟环境中虚拟人物角色的控制器;或用于在工业环境中定位人员的计划工具。

著录项

  • 作者

    Talbot, Christine.;

  • 作者单位

    The University of North Carolina at Charlotte.;

  • 授予单位 The University of North Carolina at Charlotte.;
  • 学科 Artificial intelligence.;Computer science.
  • 学位 Ph.D.
  • 年度 2018
  • 页码 260 p.
  • 总页数 260
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:53:33

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号