Computer Science Graduate Seminar: Interactive Data Annotation for Virtual Reality Applications
Monday, July 15, 2019, 4:00pm
Location: Seminar Room 001, IT Center, Kopernikusstr. 6
Speaker: Dipl.-Inform. Sebastian Pick
Virtual Reality (VR) offers the unique possibility to explore data sets in a highly immersive and interactive fashion. A key aspect of this exploration process is the acquisition of insights and findings concerning the involved data. In this context, it becomes the task of so-called annotation systems to enable users to preserve said findings and review them at a later time. Even though the design of VR-based annotation systems has been a research topic for many years, crucial challenges remain unresolved. Many interaction solutions focus on isolated issues and are rather limited in scope. Additionally, they usually forgo holistic workflow designs that are vital for covering all relevant annotation operations in a consistent fashion. Similarly, available annotation presentation techniques are usually inappropriate for use within immersive virtual environments (IVEs) or they perform sub-optimally. Lastly, the design of annotation systems is usually further complicated if they are to be reused in context of other usage scenarios that impose a different and varying set of requirements on them.
In this thesis, I set out to address the aforementioned issues. To this end, I present an annotation framework that was specifically designed to be configurable and extensible in accordance to the changing requirements of different application scenarios. It is grounded in a specialized data model that facilitates the integration not only of required data types, which are used to describe annotations, but also techniques to capture and present them. I employ this model to develop a flexible solution to the design of holistic interaction workflows. My design approach covers all essential operations, including the creation, modication, and review of arbitrary types of annotations from within IVEs. To provide a set of ready-to-use interaction techniques to acquire annotation contents, I identify the most relevant data types and devise appropriate interaction concepts. Similarly, I present a generalized two-tier presentation strategy that facilitates the access to and review of arbitrary annotation contents. While the tier one representation provides basic access to a selection of contents in a customizable form, the tier two representation allows for access to all contents in a generalized manner. I furthermore introduce a novel automated annotation layout approach that prevents occlusions of and by annotations to maintain visual access to them and the original data. In order to determine the viability of my approaches, I cover a series of technical analyses and user studies. They are rounded off by a presentation of concrete application examples that utilize varying subsets of techniques to demonstrate the usefulness and flexibility of my framework.
The computer science lecturers invite interested people to join.