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Martin Ernst Heckmann , "Inter-speaker variability in audio-visual classification of word prominence", Proc. INTERSPEECH, 2013.
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Yaochu Jin, Ke Tang, Xin Yu, Bernhard Sendhoff, Xin Yao , "A framework for finding robust optimal solutions over time", Memetic Computing, vol. 5, no. 1, pp. 3-18, 2013.
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Tobias Kühnl , "Road Terrain Detection for Advanced Driver Assistance Systems", Bielefeld University, University of Bielefeld, 2013.
AbstractIn recent years, automotive manufacturers have equipped their vehicles with innovative Advanced Driver Assistance Systems (ADAS) to ease driving and avoid dangerous situations, such as unintended lane departures or collisions with other road users, like vehicles and pedestrians. To this end, ADAS at the cutting edge are equipped with cameras to sense the vehicle surrounding. An important source of information for future ADAS is the road course, i...
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Martin Ernst Heckmann , "Differences in the audio-visual detection of word prominence from Japanese and English speakers", Proc. Int. Conf. Auditory-Visual Speech Processing, 2013.
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Christopher Priester, Kaname Narukawa, Tobias Rodemann , "A Comparison of Different Algorithms for the Calculation of Dominated Hypervolumes", Genetic and Evolutionary Computation Conf. (GECCO), 2013.
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Thomas Guthier, Adrian Sosic, Volker Willert, Julian Eggert , "sNN-LDS: Spatio-temporal Non-negative Sparse Coding for Human Action Recognition", Artificial Neural Networks andProceedings of the 24th International Conference on Artificial Neural Networks (ICANN), pp. 185-192, 2013.
AbstractCurrent state-of-the-art approaches for human action recognition focus on complex local spatio-temporal descriptors, while the spatio-temporal relations between the descriptors are discarded. This bag-of-words (BOW) based approaches come with the cost of limited descriptive power, because class-specific mid- and large-scale topological information, such as body poses, cannot be represented. To overcome this restriction, we propose sparse non-nega...
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Andreas Knoblauch, Ursula Körner, Edgar Körner , "A brain-inspired cognitive architecture for self-referential autonomous learning of situation representations.", Proceedings of the 17th International Conference on Cognitive and Neural Systems (ICCNS), 2013.
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Matthias Platho, Horst-Michael Groß, Julian Eggert , "Learning Situation Models from Velocity Profiles", IEEE Intelligent Transportation Systems Conference (ITSC), pp. 276-281, 2013.
AbstractFor an Advanced Driver Assistance System recognizing the driving situation of other vehicles is a crucial prerequisite to anticipate their behavior and plan own maneuvers accordingly. Current methods for situation recognition usually rely on an expert for defining the considered driving situations manually while solely the parameters of the corresponding behavior models are learned from observations. Unfortunately, the performance of this ...
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Thomas H Weisswange, Bram Bolder, Jannik Fritsch, Stephan Hasler, Christian Goerick , "An Integrated ADAS for Assessing Risky Situations in Urban Driving", IEEE Intelligent Vehicles Symposium 2013, 2013.
AbstractAdvanced Driver Assistance Systems (ADAS) are becoming more and more popular. Many of these systems though are limited to specific scenes and often detect risky situations very late so they can only mitigate accidents. These effects are mainly caused by the use of simple physical prediction methods, e.g. to estimate the time-to-contact with another vehicle. In this paper we show an ADAS that extends the functionality of physical collision warning...
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Matthias Platho, Horst-Michael Groß, Julian Eggert , "Predicting Velocity Profiles of Road Users at Intersections Using Configurations", Intelligent Vehicles Symposium (IV), pp. 945-951, 2013.
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