Institute of Computer ScienceOpen OpportunitiesThe increasing pervasiveness of Mixed Reality (MR) technologies and of digital services that surround us has created the need to inform users about the privacy implications of using MR applications and services. While we encounter Privacy Policies on the Web mostly in text-form, there has been research that investigates the representation of privacy policies as labels (e.g., like the Nutri-score on food products) and icons. MR devices however offer many design opportunities to display the contents of privacy policies that go beyond showing the full text in the field-of-view of a user. Additionally, it has been reported that text-only representations of privacy policies are most of the times ignored given their length and usage of complicated language. In this project, you will investigate different possibilities for effectively displaying privacy policies in MR. - Computer-Human Interaction, Research, Science and Technology Policy
- Bachelor Thesis, Master Thesis
| The increasing number of connected (IoT-) devices in everyday environments calls for methods that enables users to intuitively and homogeneously interact with them. Mixed Reality head-mounted displays, such as the Microsoft HoloLens 2, are a suitable mean, since they allow users to perform hands-free interactions and they can augment the physical space of a user. To provide a homogeneous way to interact with a plethora of devices that have been made by different manufactures, we propose the usage of the Web of Things Thing Description (TD), a standardized way of describing the programming interface of a device (Thing). - Computer-Human Interaction, Engineering and Technology
- Bachelor Thesis, Master Thesis
| The proposed project connects context-based unique IDs (CUIDs) of visually detected objects to their semantic description in Thing Descriptions (TDs). The project involves a visual perturbation (the execution of the approach might feel like activities in a ghost town to the users) to distinguish objects of similar appearances and assigns a relevant TD to each instance of the object for interaction. Additionally, TDs will be created and made available in a Knowledge Graph for discovery and use in the system. The proposed project is a continuation of an earlier project, in which, through computer vision algorithms, we were able to identify and temporally track objects and their relationships, which allowed us to describe the environment based on a contextual understanding of it. The input for the system is entirely visual and has no other sensory mode. In this situation, assigning a unique ID to the objects visible in the surrounding is challenging. The difficulty becomes evident when it comes to distinguishing between two similar-looking objects present in the scene. For this, we defined and implemented the concept of CUIDs, which are assigned to objects detected in a scene according to their relationships with other objects. To get you familiar with this previous implementation, we will provide you with the recently submitted paper on this project. - Artificial Intelligence and Signal and Image Processing
- Bachelor Thesis, Semester Project
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