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An adaptive, invariant to user performance fluctuation or noisy input signal, gesture recognition scheme is presented based on Self Organizing Maps, Markov Models and Levenshtein sequence distance. Multiple modalities, all based on the hand position during gesturing, train different classifiers which are then fused in a weak classifier boosting-like setup by weight assignment to each stream. The adaptability...
When users of computer systems are given the opportunity to provide feedback on their preferences or interests in most cases they are presented with a questionnaire to be filled. However, this means of interaction requires an additional cognitive step, since the user is required to rationalize feelings and attitudes by answering predetermined questions; as a result, users often skip this part or answer...
The paper presents the framework of a special session that aims at investigating the best possible techniques for multimodal emotion recognition and expressivity analysis in human computer interaction, based on a common psychological background. The session mainly deals with audio and visual emotion analysis, with physiological signal analysis serving as supplementary to these modalities. Specific...
Since facial expressions are a key modality in human communication, the automated analysis of facial images for the estimation of the displayed expression is essential in the design of intuitive and accessible human computer interaction systems. In most existing rule-based expression recognition approaches, analysis is semiautomatic or requires high quality video. In this paper we propose a feature...
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