Research Interests
Understanding sensor information is a fundamental problem in computer science. Scientific challenges cover the entire pipeline from single-sensor processing, over spatial and temporal fusion of multiple and divergent sensor modalities to the complete description of large-scale multimodal sensor streams. At the same time we observe a tremendous increase in both the quantity as well as the diversity of sensor information due to the increasing number of sensors (such as cameras, GPS, or inertial sensors) embedded in a wide variety of digital devices and environments as well as due to the increasing storage of multimodal sensor data (such as surveillance data, personal storage of digital information, multimedia databases, or simply the Internet). While storing and indexing large amounts of sensor data has made tremendous progress, understanding of this multimodal sensor data still lacks far behind. Therefore the long-term goal of our research is to make progress on how to process, structure, access and truly understand multi-sensory data both for online use as well as for large-scale databases.