Pregled bibliografske jedinice broj: 255682
[HUGE]: Universal Architecture for Statistically Based HUman GEsturing
[HUGE]: Universal Architecture for Statistically Based HUman GEsturing // Lecture Notes in Artificial Intelligence, 4133 (2006), 256-269 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 255682 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
[HUGE]: Universal Architecture for Statistically Based HUman GEsturing
Autori
Šmid, Karlo ; Zorić, Goranka ; Pandžić, Igor
Izvornik
Lecture Notes in Artificial Intelligence (0302-9743) 4133
(2006);
256-269
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
statistical models; facial gestures; universal architecture; inducements
Sažetak
We introduce a universal architecture for statistically based HUman GEsturing (HUGE) system, for producing and using statistical models for facial gestures based on any kind of inducement. As inducement we consider any kind of signal that occurs in parallel to the production of gestures in human behaviour and that may have a statistical correlation with the occurrence of gestures, e.g. text that is spoken, audio signal of speech, bio signals etc. The correlation between the inducement signal and the gestures is used to first build the statistical model of gestures based on a training corpus consisting of sequences of gestures and corresponding inducement data sequences. In the runtime phase, the raw, previously unknown inducement data is used to trigger (induce) the real time gestures of the agent based on the previously constructed statistical model. We present the general architecture and implementation issues of our system, and further clarify it through two case studies. We believe that this universal architecture is useful for experimenting with various kinds of potential inducement signals and their features and exploring the correlation of such signals or features with the gesturing behaviour.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus