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Hits 1 – 9 of 9
1
ORIGINAL ARTICLE Non-manual cues in automatic sign language recognition
George Caridakis
;
Stylianos Asteriadis
;
Kostas Karpouzis
In: http://www.image.ece.ntua.gr/papers/741.pdf (2011)
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2
Dynamic GSL Synthesis to Support Access to e-content
Stavroula Evita Fotinea
;
Eleni Efthimiou
;
Kostas Karpouzis
...
In: http://www.image.ece.ntua.gr/papers/332.pdf (2005)
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3
ADAPTIVE GESTURE RECOGNITION IN HUMAN COMPUTER INTERACTION
George Caridakis
;
Kostas Karpouzis
;
Nasos Drosopoulos
...
In: http://www.image.ece.ntua.gr/papers/604.pdf
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4
4 A knowledge-based sign synthesis architecture
Long Paper
;
Stavroula-evita Fotinea Eleni Efthimiou
;
George Caridakis Kostas Karpouzis
...
In: http://www.image.ece.ntua.gr/papers/425.pdf
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5
Communication and Signal Processing Group
George Caridakis
;
Olga Diamanti
;
Petros Maragos
...
In: http://www.image.ece.ntua.gr/papers/556.pdf
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6
DIANOEMA: Visual analysis and sign recognition for GSL modelling and robot teleoperation
Stavroula-evita Fotinea
;
Eleni Efthimiou
;
George Caridakis
...
In: http://www.image.ece.ntua.gr/papers/582.pdf
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7
eds.): A Knowledge-based Sign Synthesis Architecture. Emerging Technologies for Deaf Accessibility
Long Paper
;
George Caridakis
;
Æ Kostas Karpouzis
...
In: http://www.image.ece.ntua.gr/papers/425.pdf
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8
User modeling via gesture and head pose expressivity features
George Caridakis
;
Kostas Karpouzis
;
Stylianos Asteriadis
In: http://www.image.ece.ntua.gr/papers/652.pdf
Abstract:
Current work focuses on user modeling in terms of affective analysis that could in turn be used in intelligent personalized interfaces and systems, dynamic profiling and context-aware multimedia applications. The analysis performed within this work comprises of statistical processing and classification of automatically extracted gestural and head pose expressivity features. Computational formulation of qualitative expressive cues of body and head motion is performed and the resulting features are processed statistically, their correlation is studied and finally an emotion recognition attempt is presented based on these features. Significant emotion specific patterns and expressivity features interrelations are derived while the emotion recognition results indicate that the gestural and head pose expressivity features could supplement and enhance a multimodal affective analysis system incorporating an additional modality to be fused with other commonly used modalities such as facial expressions, prosodic and lexical acoustic features and physiological measurements. 1
URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.186.2469
http://www.image.ece.ntua.gr/papers/652.pdf
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9
Multimodal Emotion Recognition from Low-Level Cues
Maja Pantic
;
George Caridakis
;
Elisabeth André
...
In: http://www.image.ece.ntua.gr/papers/635.pdf
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