Students, especially international ones have a hard time seeking accommodation in big cities like Stockholm in Sweden at an adequate pricing. To facilitate such a search process and to create a sense of trust, tenants and landlords use video and/or voice calls for early communication with one another. However, the establishment of trust among tenants and landlords in this context is a challenging task. This study thus aims to investigate if innovative virtual reality (VR) approaches like 360° videos can be used to develop trust among tenants and landlords. This study undertakes an investigation from student perspective due to the limited timeframe. This study was carried out in collaboration with Ett tak (English: One roof) which is a startup working in the rental market in Stockholm. The tenants are the students and the landlords are senior people having spare space in their homes. A pre-study was conducted to identify the expectations of the students. A landlord was filmed for the 360° video which was developed into a Unity VR app. The results from the usability study indicate that most students felt a high degree of trust towards the landlord by using an immersive 360° VR tour. Conversely, the students showed hesitation to use the 360° VR by buying their own VR headsets unless VR becomes mainstream in the different areas of life. This study builds upon existing literature that validate the positive impact of attributes like profile photos, ratings and reviews on the trust level between the providers and the consumers in a sharing economy. / Studenter, särskilt internationella, har svårt att hitta boende i storstäder som Stockholm i Sverige till lämplig prissättning. För att underlätta en sådan sökprocess och skapa en känsla av förtroende använder hyresgäster och hyresvärdar video och / eller röstsamtal för tidig kommunikation med varandra. Upprättande av förtroende bland hyresgäster och hyresvärdar är dock en utmanande uppgift i detta sammanhang. Denna studie syftar således till att undersöka om virtuell verklighet (VR) som 360° video kan användas för att utveckla förtroende bland hyresgäster och hyresvärdar. Denna studie genomför en undersökning från ett studentperspektiv på grund av den begränsade tidsramen. Denna studie genomfördes i samverkan med Ett tak, som arbetar på hyresmarknaden i Stockholm. Hyresgästerna är studenterna och hyresvärdarna är äldre människor som har ledigt utrymme i sina hem. En förstudie genomfördes för att identifiera studenternas förväntningar. En hyresvärd filmades för en 360° video som utvecklades till en Unity VR app. Resultaten från användbarhetsstudien indikerar att de flesta studenter kände en hög grad av förtroende gentemot hyresvärden genom att använda en fördjupande 360 ° VR rundtur. Däremot visade eleverna att de inte skulle köpa egna VR-headset om VR inte blir vanligt i de olika områdena i livet. Denna studie bygger på befintlig litteratur och bekräftar den positiva effekten av attribut som profilbilder, betyg och recensioner på förtroendenivå mellan leverantörer och konsumenter i en delningsekonomi.

In this thesis we explore the concepts and components which can be used as individual building blocks for producing immersive virtual reality (VR) content from a single RGB-D sensor. We identify the properties of immersive VR videos and propose a system composed of a foreground/background separator, a dynamic scene re-constructor and a shape completer. We initially explore the foreground/background separator component in the context of video summarization. More specifically, we examined how to extract trajectories of moving objects from video sequences captured with a static camera. We then present a new approach for video summarization via minimization of the spatial-temporal projections of the extracted object trajectories. New evaluation criterion are also presented for video summarization. These concepts of foreground/background separation can then be applied towards VR scene creation by extracting relative objects of interest. We present an approach for the dynamic scene re-constructor component using a single moving RGB-D sensor. By tracking the foreground objects and removing them from the input RGB-D frames we can feed the background only data into existing RGB-D SLAM systems. The result is a static 3D background model where the foreground frames are then super-imposed to produce a coherent scene with dynamic moving foreground objects. We also present a specific method for extracting moving foreground objects from a moving RGB-D camera along with an evaluation dataset with benchmarks. Lastly, the shape completer component takes in a single view depth map of an object as input and "fills in" the occluded portions to produce a complete 3D shape. We present an approach that utilizes a new data minimal representation, the additive depth map, which allows traditional 2D convolutional neural networks to accomplish the task. The additive depth map represents the amount of depth required to transform the input into the "back depth map" which would exist if there was a sensor exactly opposite of the input. We train and benchmark our approach using existing synthetic datasets and also show that it can perform shape completion on real world data without fine-tuning. Our experiments show that our data minimal representation can achieve comparable results to existing state-of-the-art 3D networks while also being able to produce higher resolution outputs.