PhD Theses

The subsequently listed PhD theses are currently being performed within the MADMACS project or have been completed as part of this group.

Robert Neßelrath: „An open platform for the model-based development of dialogue applications with distributed input and output in cyber-physical systems“

Cyber-Physical systems integrate computational elements into the physical world. An increasing number of interconnected human-computer interfaces, sensors and actuators in the intelligent environment enable new HCI concepts supporting multimodal distributed input and output.

The major contribution of the dissertation is the SiAM dialogue platform (SiAM-dp) that contains a fully tool-supported development environment for multimodal dialogue applications with a high flexibility in the mode and number of connected devices. A model-based approach supports the rapid creation of new multimodal user interfaces independently from the domain and applied devices.

Introducing smart and modern interaction concepts requires a system that supports both the information from various input modalities as well as the description of physical acts. Additionally the actual context of the dialogue, participants, and the environment can provide valuable information for the resolution of uncertain, missing, or implicitly given content or can influence the course of the further interaction. The thesis analyzes how the semantic representation of knowledge, user intentions, and events can be exploited for the fusion of multimodal user input, physical acts, and context knowledge.)

M. Mehdi Moniri: „Real-Time Multimodal Reference Resolution in Indoor and Outdoor Environments“

Within the scope of the dissertation of Mohammad Mehdi Moniri different algorithms and methods for driver monitoring, vehicle positioning and fusion of various sensor sources are developed. This system will make it possible to determine exactly which objects in the environment (at the given time) were visible to the driver and for how long. In addition, this system conducts a scene analysis for different driving situations by fusion of different information sources such as driver’s focus-of-attention and road context. This research prototype aims to achieve a significant increase in the safety of road and to improve the usability of infotainment systems.