박혜림

불완전한 기억의 공간 가시화 재구성 기술 개발

We investigate how path context, encompassing both comfort and attractiveness, shapes user experiences in outdoor locative storytelling using Augmented Reality (AR). Addressing a research gap that predominantly concentrates on indoor settings or narrative backdrops, our user-focused research delves into the interplay between perceived path context and locative AR storytelling on routes with diverse walkability levels. We examine the correlation and causation between narrative engagement, spatial presence, perceived workload, and perceived path context. Our findings show that on paths with reasonable path walkability, attractive elements positively influence the narrative experience. However, even in environments with assured narrative walkability, inappropriate safety elements can divert user attention to mobility, hindering the integration of real-world features into the narrative. These results carry significant implications for path creation in outdoor locative AR storytelling, underscoring the importance of ensuring comfort and maintaining a balance between comfort and attractiveness to enrich the outdoor AR storytelling experience.

There have been studies on personalized augmented reality (AR) systems taking users’ contexts and histories into account. However, there is insufficient research on incorporating real-time user behavior and interactions into the personalized recommendations in spatial transitions, which can be used for new users without user history data. The spatial transitions, distances between two Point of Interests (POIs) of an AR tour trajectory through which users should pass to visit AR contents, need to be filled using the personalized AR contents to reduce the discontinuity experience. This paper aims to propose a user behavior model to recommend personalized contents in the AR tour trajectory to create a personalized experience. First, we model three interactions, including staring, skipping, and liking, using mathematical methods; and two spatial behaviors, including standing and moving, using a rule engine. Second, a content filtering-based recommendation method is presented to apply the proposed user model to recommend personalized AR contents in the spatial transitions. The experiment results showed that the proposed real-time user behavior model brought notable improvements in creating a personal experience of the AR tour system. The proposed method outperformed the conventional method in terms of recommendation performance metrics, so that it achieved an average of 15% more precision and recall scores and an average of 32% more personalization scores than those of the conventional method. Furthermore, the level of personalization perceived by the proposed user model demonstrated significant positive relationships with the level of decision effectiveness, system trustworthiness, and perceived recommendation transparency. The findings showed the effectiveness of the proposed framework in solving the cold-start recommendation problem.

There have been attempts to provide new cinematic experiences by connecting TV or movie content to suitable locations through augmented reality (AR). However, few studies have suggested a method to manage breakdowns in continuity due to spatial transitions. Thus, we propose a method to manage the spatial transition that occurs when we create a TV show trajectory by mapping TV show scenes with spatiotemporal information to the real world. Our approach involved two steps. The first step is to reduce the spatial transition considering the sequence, location, and importance of TV show scenes when creating the TV show trajectory in the authoring tool. The second is to fill the spatial transition with additional TV show scenes considering sequence, importance, and user interest when providing the TV show trajectory in the mobile application. The user study results showed that reducing spatial transition increases narrative engagement by allowing participants to see important content within the trajectory. The additional content in spatial transition decreased the physical demand and effort in terms of the perceived workload, although it increased the task completion time. Integrated spatial transition management improved the overall cinematic augmented reality (CAR) experience of the TV show. Furthermore, we suggest design implications for realizing the CAR of TV shows based on our findings.

Most research on providing location-based content in 3D interactive virtual reality has been limited to social media content. Few studies have suggested how to represent the video clip of movies or TV shows in virtual reality. This paper investigates a video content representation method to provide a hyper-reality experience of the narrative world in virtual reality. We reflect the time and place settings of the video content in virtual reality and have participants watch the video in four different virtual reality environments. We reveal that reflecting the story's environment settings to the virtual reality environment significantly improves the spatial presence and narratives engagement. We also confirm a positive correlation between spatial presence and narrative engagement, including subscales such as emotional engagement and narrative presence. Based on the study results, we discuss how to provide the hyper-reality experience in content-adaptive virtual reality.

There have been a number of researches to provide new media experience through augmented reality technology. However, most of them focus on creating new virtual content rather than remediating existing content such as films and TV programs. In this paper, we design a metadata schema and use cases to provide location-based film experience based on the Spacetelling framework. To evaluate the metadata, we implement the application based on the relational database of the proposed metadata schema and provide it to visitors in the historical site. By analyzing users' requirements, we could find that the metadata properties provide new and valuable media experience in terms of affective, cognitive, and operative aspects. People felt more familiar with and interested in the place by watching movie clips in the related place. As a result, we suggest the design guideline derived from the experiment.

In recent years, augmented-reality (AR) has been attracting extensive attentions from both the research community and industry as a new form of media, mixing virtual content into the physical world. However, the scarcity of the AR content and the lack of user contexts are major impediments to providing and representing rich and dynamic multimedia content on AR applications. In this study, we propose an approach to search and filter big multimedia data, specifically geo-tagged mobile videos, for context-aware AR applications. The challenge is to automatically search for interesting video segments out of a huge amount of user-generated mobile videos, which is one of the biggest multimedia data, to be efficiently incorporated into AR applications. We model the significance of video segments as AR content adopting camera shooting patterns defined in filming, such as panning, zooming, tracking and arching. Then, several efficient algorithms are proposed to search for such patterns using fine granular geospatial properties of the videos such as camera locations and viewing directions over time. Experiments with real-world geo-tagged video dataset show that the proposed algorithms effectively search for a large collection of user-generated mobile videos to identify top K significant video segments.