Katrin Lohan, Sebastian Gieselmann, Anna-Lisa Vollmer, Katharina Rohlfing, Britta Wrede,
"Does embodiment affect tutoring behavior?",
Proc. IEEE 9th Int Development and Learning (ICDL) Conf, 2010.
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Miranda Grahl, Frank Joublin, Franz Kummert,
"A method for visual model learning during tracking",
Int. Conf. on Neural Information Processing (ICONIP), 2010.
Abstract
In this paper, we propose a new method for visual model learning. The algorithm learns an object representation by one-shot and adaptively extends a set of saliency filters. The filter coefficients are extracted from the environment by different views. In addition, the algorithm fuses already learned visual filters and derives new visual classifiers in order to gain generalized object concepts. We evaluate our method on tracked sequences that are...
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Volker Willert and Julian Eggert,
"Dynamic Visual Motion Estimation",
Probabilistic Methods for Motion Extraction (tentative), 2010.
Abstract
Visual motion is the projection of scene movements on a visual sensor. It is a rich source of information for the analysis of a visual scene. Especially for dynamic vision systems the estimation of visual motion is important because it allows to deduce the motion of objects as well as the self-motion of the system relative to the environment. Therefore, visual motion serves as a basic information for navigation and exploration tasks, like obstacl...
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Gökhan Ince, Kazuhiro Nakadai, Tobias Rodemann, Hiroshi Tsujino, Jun-ichi Imura,
"Multi-talker Speech Recognition under Ego-motion Noise using Missing Feature Theory",
IEEE-RSJ International Conference on Intelligent Robot and Systems (IROS 2010), 2010.
Abstract
This paper presents a system that gives a mobile robot the ability to recognize target speaker's speech, even if the robot performs an action and there are multiple speakers talking in the room. Associated problems to this system are twofold: (1) While the robot is moving, the joints inevitably generate ego-motion noise due to its motors. (2) Recognizing target speech against other interfering speech signals is a difficult task. Since typical sol...
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Alexander Denecke, Irene Clemente, Heiko Wersing, Julian Eggert, Jochen Steil,
"Figure-ground Segmentation using Metrics Adaptation in Level Set Methods",
European Symposium on Artificial Neural Networks (ESANN), 2010.
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Chen Zhang and Julian Eggert,
"Exploiting Hierarchical Prediction Models for Mixed 2D-3D Tracking",
European Symposium on Artificial Neural Networks (ESANN), 2010.
Abstract
In this paper, we present a generic way to use a hierarchical representation of prediction models for adaptive tracking. Starting with a basic appearance-based tracker working in 2D retinal space, we show how to combine individual trackers for the left and right eye to a true 3D tracker that is built on top of the 2D trackers. We show how the trackers benefit from the hierarchical structure by dynamical model switching depending on the reliabilit...
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Thomas Michalke, Robert Kastner, Jannik Fritsch, Christian Goerick,
"A Self-Adaptive Approach for Curbstone/Roadside Detection based on Human-Like Signal Processing and Multi-Sensor Fusion",
IEEE Intelligent Vehicles Symposium (IV), 2010.
Abstract
Newly emerging, highly complex Advanced Driver Assistance Systems (ADAS) fuse the output of various system modules (e.g., lane detection, object classification). Such knowledge fusion is realized in order to gain additional information of the environment allowing for complex system tasks as path planning, the active search for specific objects and task-specific analysis of the environment. As part of our previous work, we realized a highly generi...
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Daniel Dornbusch, Robert Haschke, Stefan Menzel, Heiko Wersing,
"Correlating Shape and Functional Properties Using Decomposition Approaches",
23rd Florida Artificial Intelligence Research Society Conference (FLAIRS-23), pp. 398 – 403, 2010.
Abstract
In this paper, we propose the application of standard decomposition approaches to find local correlations in multimodal data. In a test scenario, we apply these methods to correlate the local shape of turbine blades with their associated aerodynamic flow fields. We compare several decomposition algorithms, i.e., k-Means, Principal Component Analysis, Non-negative Matrix Factorization and Uni-orthogonal Non-negative Matrix Factorization, with rega...
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Tobias Rodemann, Martin Heckmann, Claudius Gläser, Frank Joublin, Christian Goerick,
"Towards Speech Acquisition in Natural Interaction on ASIMO",
Journal of the Robot Society of Japan, special issue on Robot Audition, vol. 28, no. 1, pp. 18–22, 2010.
Abstract
The standard approach for teaching robots to communicate via speech is by providing the structure, statistics, and semantics of speech through a supervised, offline learning process. This process imposes constraints like a high degree of specialization to certain, predefined tasks. The resulting system is very rigid and lacks the ability to acquire new skills (e.g. words and their semantics). In contrast to this, children acquire language through...
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Xavier Domont,
"Hierarchical Spectro-Temporal Features for Robust Speech Recognition",
Technische Universität Darmstadt, 2010.
Abstract
Automatic Speech Recognition (ASR) systems are nowadays integrated into products like computer operating systems, automobiles, or hotlines. ASR system are for instance used by p hysicians for el ectronic medical record where it replaces tr aditional dictation and subsequent secretarial transcription [1]. The survey in [1] shows that the physicians tend to be less enthusiastic with the introduction of the new technology after having used it for so...
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