Using personal data for AR driven story telling

我将首先调查当前的文献，关于哪些故事正在讲述或预测将在混合现实媒体（MRM;用于描述VR和AR）中讲述，以及当前和不久的将来技术的哪些功能允许有效地讲述故事。在这一点上，对以前的MRM（如Shilkrot et al（2014）和Zhou et al（2008））的荟萃分析将非常重要。这篇文献综述将为我的研究的下一步提供信息，即创建两种混合现实体验。其中一个体验将利用360度视频从多个角度捕捉现场戏剧表演，以便观众可以决定从表演空间之外的地方观看表演。另一个将计算机生成一个版本的现场戏剧表演，无论是使用动作捕捉或自由视点视频（Collet等人，2015年详细介绍），以便观众可以在表演空间中移动，并从任何角度观看。一旦这些体验被创造出来，参与者将被招募来观看它们，以当前和不久的将来的头戴式耳机能够实现的多种方式来记录观看期间他们的行为。他们的注意力放在体验中的哪里，以及多长时间，将使用LaValle等人（2014）和眼动跟踪技术中描述的跟踪头部定位来计算。如果他们在体验过程中说了什么或笑或尖叫，这对内容创作者来说也是有用的信息，因此板载麦克风将记录这些数据。我们还将使用调查和访谈。然后将检查这些受众反馈数据，并将其用于第二轮内容创作，在第二轮内容创作中，将根据这些反馈重新创建体验，以改进体验，使其更受欢迎，更吸引眼球或更吸引人。这些新的和改进的体验将由新的和以前的参与者进行审查，并再次收集观看行为数据，以查看观众反馈是否能够为更吸引人的内容创作过程提供信息。这个博士学位很重要，因为MRM使用全新的消费者技术来讲述故事，与其他传统媒体技术相比具有独特的功能，例如增加创造性互动的范围（Nam，2015年）。虽然这项技术的应用正在被广泛研究，但研究它们的下一步是开发可以收集有关观众行为的数据并将这些数据反馈给内容创作者和广播公司的系统，以告知未来的节目（例如，我的项目合作伙伴BBC热衷于研究讲故事和参与AR的HCI）。这样做使我能够站在调查这项新技术如何为未来观众塑造故事的最前沿。

I will first investigate the current literature concerning which stories are being told or predicted to be told in mixed reality media (MRM; used to describe both VR and AR), as well as which features of current and near future technology allow for stories to be told effectively. Meta-analyses of previous MRM, such as those by Shilkrot et al (2014) and Zhou et al (2008), will be very important at this point.This literature review will then inform the next steps of my research namely the creating of two mixed reality experiences. One of these experiences will utilise 360 degree video to capture a live theatre performance from multiple angles, so that the audience can decide where to view a performance from outside the performance space. The other will computer generate a version of a live theatre performance, either using motion capture or free viewpoint video (detailed in Collet et al, 2015), so that audiences can move throughout the performance space while it is happening and view it from any angle.Once these experiences have been created participants will be recruited to view them, with their behaviour during the viewing being recorded in a number of ways that current and near future headsets are able to. Where their attention is placed in the experience, and for how long, will be figured out using tracked head positioning, described in LaValle et al (2014) and eye tracking technology. If they say anything or laugh or scream during the experience this is also useful information for content creators so on board microphones will record this data. Surveys and interviews will also be used.This audience feedback data will then be examined and used to inform the second round of content creation, where the experiences are recreated with this feedback in mind to improve them and make them more preferred and attention grabbing, or engaging. These new and improved experiences will then be reviewed by a mixture of new and previous participants and viewing behaviour data collected again to see if the audience feedback was able to inform a more engaging content creation process.This PhD is important because MRM use brand new consumer technology for storytelling with unique features compared to other traditional media technologies, such as the increased scope for creative interactivity (Nam, 2015). Although applications of this technology are being studied quite widely the next step in researching them is developing systems that can collect data about audience behaviour and feed this data back to content creators and broadcasters to inform future programming (for example the BBC, my project partner, is keen to look at storytelling and the HCI of engagement in AR). Doing this allows me to be at the forefront of investigating how this new technology can shape stories for future audiences.