360-degree image and movie content has gained popularity over the media and the MICE (Meeting, Incentive, Conventions, and Exhibitions) industry in the last few years. There are three main reasons for this development. First, on the one hand, it is the immersive character of this media form, and, on the other hand, the development of recording and presentation technology has made significant progress in terms of resolution and quality. Third, after a decade of dynamic rising, the MICE Industry focuses on a disruptive change for more digital-based solutions. 360-degree panoramas are particularly widespread in VR and AR technology. However, despite the high immersive potential, these forms of presentation have the disadvantage that the users are isolated and have no social contact during the performance. Therefore, efforts have been made to project 360-degree content in specially equipped rooms or planetariums to enable a shared experience for the audience. One application area for 360-degree panoramas and films is conference rooms in hotels, conference centers, and any other venues that create an immersive environment for their clients to stimulate creativity. This work aims to overview the various application scenarios and usability possibilities for such conference rooms. In particular, we consider applications in construction, control, tourism, medicine, art exhibition, architecture, music performance, education, partying, organizing and carrying out events, and video conferencing. These applications and use scenarios were successfully tested, implemented, and evaluated in the 360-degree conference room “Dortmund” in the Hotel Park Soltau in Soltau, Germany. Finally, the advantages, challenges, and limitations of the proposed method are described.
Viewport prediction technologies are often used by most popular adaptive 360-degree video streaming solutions. These solutions stream only the content considered as being more likely to be watched by the final user, with the goal of reducing the volume of network traffic without compromising the user’s Quality of Experience (QoE). In this paper, we propose the Most Viewed Cluster algorithm (MVC), which is a hybrid viewport prediction method. It estimates the user viewport using two types of information: (i) the path of moving objects in the scene and (ii) the viewing behavior of previous users. Preliminary results show that MVC yields good results for long-term predictions.