Martin Heracles

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— We introduce our latest autonomous learning and interaction system instance ALIS 2. It comprises different sensing modalities for visual (depth blobs, planar surfaces, motion) and auditory (speech, localization) signals and self-collision free behavior generation on the robot ASIMO. The system design emphasizes the split into a completely autonomous(More)
— Man-made real-world environments are dominated by planar surfaces many of which constitute behavior-relevant entities. Thus, the ability to perceive planar surfaces is vital for any embodied system operating in such environments, be it human or robotic. In this paper, we present an architecture for detection and estimation of planar surfaces in the scene(More)
— A stable perception of the environment is a crucial prerequisite for researching the learning of semantics from human-robot interaction and also for the generation of behavior relying on the robots perception. In this paper, we propose several contributions to this research field. To organize visual perception the concept of proto-objects is used for the(More)
We propose a method for vision-based scene understanding in urban traffic environments that predicts the appropriate behavior of a human driver in a given visual scene. The method relies on a decomposition of the visual scene into its constituent objects by image segmentation and uses segmentation-based features that represent both their identity and(More)
— In this paper we propose a system architecture that extends the current state-of-the-art in computational visual attention by incorporating the biological concept of ventral attention. According to recent findings regarding the neuro-biological foundations of attention, there exist two separate but interacting attention systems in the human brain: the(More)
A scene exploration which is quick and complete according to current task is the foundation for most higher scene processing. Many specialized approaches exist in the driver assistance domain (e.g. car recognition or lane marking detection), but we aim at an integrated system , combining several such techniques to achieve sufficient performance. In this(More)
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