Using personal data for AR driven story telling

我将首先调查目前的文献，关于混合现实媒体(MRM；用于描述VR和AR)正在讲述或预测将讲述哪些故事，以及当前和不久的将来技术的哪些特征允许有效地讲述故事。在这一点上，对以前的MRM的元分析，如Shilkrot等人(2014)和周等人(2008)的分析，将是非常重要的。这一文献综述将为我的下一步研究提供信息，即创造两种混合现实体验。其中一种体验是利用360度视频从多个角度捕捉剧院现场表演，这样观众就可以决定在表演空间之外的哪里观看表演。另一种是用计算机生成现场剧院表演的版本，使用动作捕捉或免费视点视频(详见Collet等人，2015)，这样观众就可以在表演空间中移动，从任何角度观看。一旦创建了这些体验，参与者将被招募来观看它们，观看过程中的行为将被记录下来，这是目前和不久的将来耳机所能做到的。他们的注意力放在体验中的哪里，以及放置多长时间，将使用LaValle等人(2014)中描述的跟踪头部定位和眼球跟踪技术来确定。如果他们在体验过程中说了什么，或者大笑或尖叫，这也是内容创作者的有用信息，因此机上的麦克风将记录这些数据。调查和访谈也将被使用。然后，这些观众反馈数据将被检查并用于为第二轮内容创作提供信息，在第二轮内容创作中，在考虑到这些反馈的情况下重新创建体验，以改进它们，使它们更受欢迎和吸引注意力，或吸引人。然后，这些新的和改进的体验将由新的和以前的参与者以及再次收集的观看行为数据进行审查，以确定观众反馈是否能够为更具吸引力的内容创作过程提供信息。这一博士学位很重要，因为与其他传统媒体技术相比，MRM使用全新的消费者技术来讲故事，具有独特的功能，例如增加了创造性互动的范围(NAM，2015)。尽管这项技术的应用正得到相当广泛的研究，但研究它们的下一步是开发系统，该系统可以收集观众行为的数据，并将这些数据反馈给内容创作者和广播公司，为未来的节目提供信息(例如，我的项目合作伙伴英国广播公司(BBC)热衷于研究讲故事和AR中参与的人机界面)。这样做可以让我站在研究这项新技术如何为未来观众塑造故事的前沿。

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.