Research areas:
Visual Attention
Visual attention is the selection process in human vision which directs the
gaze to the
currently most interesting data. This might be regions which "pop out" of the
image automatically, as in the picture on the left (bottom-up), or cues which are of
current interest due to motivations, emotions or goals (top-down).
more...
Object and Person Tracking
Object tracking is an important task in many computer vision and robotic
applications. It is especially difficult if not only the object but also the
camera is mobile, as for tracking from a mobile
robot. We are currently working on robust tracking methods which are based on a
combination of
feature saliencies and Particle filters. A special case is person tracking. It
is necessary for mobile robots which have to follow a person as well as for
robots which guide a person and which have to make sure that the guided person
is still following.
more...
Simultaneous Localization And Mapping
Visual Simultaneous Localization And Mapping (SLAM) is
the task of automatically creating a map of the environment from image data
without knowing the current exact position of the camera. It is usually of interest for
mobile robots but can also be applied to hand-held cameras. We developed a
visual SLAM system which finds salient landmarks, tracks them over frames and
redetects them when returning to a known position. Active camera control
improves the system performance.
more...
Completed Projects
Object Recognition
We combined an AdaBoost based object classifier with the visual attention
system VOCUS. This speeds up object recognition and reduces the number of false detections.
In [Frintrop et al. IROS 2004] we applied this approach to data from a 3D laser
scanner to recognize objects as chairs and robots. In
[Mitri et al. ICRA 2005]
we found different kinds of balls for robot soccer (RoboCup). While the
classifier detects balls based on shape, the top-down attention could be easily
trained from few training images to differently colored types of balls. This
makes the system flexible.
For details see publication list.
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