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Preface Knowledge representation and use has been a central concern for computer vision since decades. This topic becomes even more important as it is now possible to augment the reality thru real-time computer graphics in combination with real-time computer vision. As both disciplines need to cooperate, they also need to agree on common representation(More)
Traditionally, the programming of bot behaviors for commercial computer games applies rule-based approaches. But even complex or fuzzyfied automatons cannot really challenge experienced players. This contribution examines whether bot programming can be treated as a pattern recognition problem and whether behaviors can be learned from recorded games. First,(More)
Interpretation of complex scenes involves analysing multiple objects being composed of several parts. Since diierent objects often have parts in common it is useful to share resources representing these identical substructures. This is quite a diicult task for artiicial neural networks (ANNs) 4], but can be handled with semantic networks. They are a well(More)
The aim of this work is to exploit regular structure in a scene by using the gestalt laws of perception in the eld of computer vision. The statistical result of a hand labelled training set is employed to derive \Areas of perceptual attentiveness". Grouping hypotheses are thus generated based on local evidence. To judge these hypotheses in a more global(More)
The recognition of hands and the 3-dimensional characterization of hand orientation is a diicult and practically important vision problem. In this work we propose a hybrid system attaching artiicial neural networks to concepts of a semantic network to solve this problem. The neural networks are attached as a holistic representation at varying levels of the(More)
– Especially in recognition of spontaneous speech it is necessary to cope with the occurrence of unknown words. We present an approach to unknown word detection which is integrated into a standard HMM speech recognizer. From the context dependent sub-word units, e.g. triphones, that can be found in the training database a generic word model can be derived(More)
The development of autonomous as well as situated robots is one of the great remaining challenges and involves a number of different scientific disciplines. In spite of recent dramatic progress, it remains worthwhile to examine natural systems, because their abilities are still out of reach. Motivated by research work done in the fields of cognitive(More)
In this paper we propose an architecture of an image understanding system for a situated artiicial communicator realizing human-machine interaction. Starting with sensor input the processing is initially carried out in separate pathways using diierent schemes of image seg-mentation. Subsequently, a hybrid technique for 2D-object recognition is employed. The(More)
This article presents the speech understanding and dialog system EVAR. All levels of linguistic knowledge are used both to control the analysis process and for the interpretation of an utterance. All kinds of knowledge are integrated in a homogeneous knowledge base. The control algorithm used for the analysis is deened within the representation scheme and(More)