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Research Areas


Computer vision finds itself at an exciting stage of its development. Many of its areas are approaching sufficiently high performance levels to become useful for real-world applications, and numerous interesting connections are opening up to related fields such as machine learning, graphics, and mobile robotics. Moreover, instead of only focusing on a single area and advancing it through step-by-step progress, it now becomes possible for the first time to combine many different vision capabilities and explore the benefits that can be reaped in through their close integration.

Our research aims exactly at this interface. The central theme of our work is the connection of different areas of computer vision and graphics into so-called "cognitive loops", collaborative feedback cycles in which multiple vision modalities mutually support each other in order to solve a bigger task than any could do on its own. Object recognition takes a key role in this integration, since it can deliver a semantic interpretation of the image content, which considerably simplifies other tasks such as segmentation, 3D reconstruction, and tracking. In some cases, such connections are even required in order to render complex applications possible in the first place. In return, those other vision capabilities deliver additional information which again constrains and improves the recognition results.

The main application area of our work are vision services for mobile devices and robotic or automotive platforms. Imagine being able to use your cell phone's camera as an interface to the real world, pointing it to objects and buildings of interest in your surroundings and directly getting back target-specific information from internet sources without having to type a query. Or imagine your car being able to sense other traffic participants in its surroundings, enhancing safety from collisions or even taking over the driving task entirely. In our group, we are developing core technologies for such applications. Concretely, we have already made the following important steps towards this goal.

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