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Cem Karaoguz, Andrew Dankers, Tobias Rodemann, Mark Dunn , "An Analysis of Depth Estimation within Interaction Range", IEEE-RSJ International Conference on Intelligent Robot and Systems (IROS 2010), 2010.
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Christian Lang, Sven Wachsmuth, Heiko Wersing, Marc Hanheide , "Facial expressions as feedback cue in human-robot interaction - a comparison of human and automatic recognition performances", CVPR Workshop for Human Communicative Behavior Analysis, 2010.
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Claudius Gläser, Martin Ernst Heckmann, Frank Joublin, Christian Goerick , "Combining Auditory Preprocessing and Bayesian Estimation for Robust Formant Tracking", IEEE Transactions on Audio, Speech, and Language Processing, vol. 18, no. 2, pp. 224–236, 2010.
AbstractWe present a framework for estimating formant trajectories. Its focus is to achieve high robustness in noisy environments. Our approach combines a preprocessing based on functional principles of the human auditory system and a probabilistic tracking scheme. For enhancing the formant structure in spectrograms we use a Gammatone filterbank, a spectral preemphasis, as well as a spectral filtering using Difference-of-Gaussians (DoG) operators. Finall...
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Nils Einecke and Julian Eggert , "A Two-Stage Correlation Method for Stereoscopic Depth Estimation", Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, DICTA 2010, 2010.
AbstractThe computation of stereoscopic depth is an important field of computer vision. Although a large variety of algorithms has been developed, the traditional correlation-based versions of these algorithms are prevalent. This is mainly due to easy implementation and handling but also to the linear computational complexity, as compared to more elaborated algorithms based on diffusion processes, graph-cut or bilateral filtering. In this paper, we intro...
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Andreas Knoblauch, Günther Palm, Friedrich Sommer , "Memory capacities for synaptic and structural plasticity.", Neural Computation, vol. 22, no. 2, pp. 289–341, 2010.
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Gökhan Ince, Kazuhiro Nakadai, Tobias Rodemann, Yuji Hasegawa, Hiroshi Tsujino, Jun-ichi Imura , "A Hybrid Framework for Ego Noise Cancellation of a Robot", 2010.
AbstractNoise generated due to the motion of a robot is not desired, because it deteriorates the quality and intelligibility of the sounds recorded by robot-embedded microphones. It must be reduced or cancelled to achieve automatic speech recognition with a high performance. In this work, we divide ego-motion noise problem into three subdomains of arm, leg and head motion noise, depending on their complexity and intensity levels. We investigate methods t...
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Michael Gienger, Christian Goerick, Edgar Körner , "Movement control in biologically plausible frames of reference", ISR / Robotik 2010, 2010.
AbstractBiological findings suggest that human movement is encoded in a variety of action-oriented reference frames. In contrast, robotics movement control is mostly formulated in traditional frames of reference, such as the world frame, or a robotfixed base frame. In this contribution, we will investigate these biological findings and propose a movement control formulation for redundant robots that are equipped with one or several effectors. We will sho...
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Stephan Kirstein, Heiko Wersing, Edgar Körner , "Towards autonomous bootstrapping for life-long learning categorization tasks", Proceedings International Joint Conference on Neural Networks, 2010.
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Till Steiner , "Articial Evolutionary Development", Thesis of the University Bielefeld, University Bielefeld, 2010.
AbstractThis thesis is situated in the field of Artificial Development coupled to evolutionary computation. I discuss the problem of finding a suitable abstraction level for the developmental process in engineering design. Here, suitable refers to the capability to produce non-trivial artifacts, while keeping the developmental process and its formation comprehensible. Throughout this thesis, I distinguish between two components of development: The first ...
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Volker Willert and Julian Eggert , "Adaptive Velocity Tuning for Visual Motion Estimation", European Symposium on Artificial Neural Networks (ESANN), 2010.
AbstractIn the brain, both neural processing dynamics as well as the perceptual interpretation of a stimulus can depend on sensory history. The underlying principle is a sensory adaptation to the statistics of the input collected over a certain amount of time, allowing the system to tune its detectors, e.g. by improving the sampling of the input space. Here we show how a generative formulation for the problem of visual motion estimation leads to an onlin...
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