Pregled bibliografske jedinice broj: 525717
Accelerometer-Based Gesture Classification Using Principal Component Analysis
Accelerometer-Based Gesture Classification Using Principal Component Analysis // Proceedings of SoftCOM 2011
Dubrovnik, Hrvatska; Hvar, Hrvatska; Split, Hrvatska, 2011. (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 525717 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Accelerometer-Based Gesture Classification Using Principal Component Analysis
Autori
Marasović, Tea ; Papić, Vladan
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of SoftCOM 2011
/ - , 2011
ISBN
978-953-290-027-9
Skup
19th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2011)
Mjesto i datum
Dubrovnik, Hrvatska; Hvar, Hrvatska; Split, Hrvatska, 15.09.2011. - 17.09.2011
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
accelerometer; gesture recognition; principal component analysis
Sažetak
Gestures, such as a wave or a nod, are commonly used in daily lives. While gestures are most often used just as a support for our verbal communication, they can also be used as a sole, simple and effective way of communication. Recent developments in sensor technology, that have reduced the costs of small and precise sensors and allowed them to be built in a growing number of everyday devices, have also made it possible to explore and experiment with new modalities of communication in the area of human computer interaction. In the case of mobile devices, gesture-based interaction can be helpful for overcoming the physical size limitations, which make the usage of such devices particularly tedious. In this paper we propose a system that uses the accelerometer, embedded in a mobile phone, to capture simple gestures, such as hand describing a circle, thus allowing the user to draw or even write in the air. The principle component analysis is used for feature selection and dimensionality reduction in gesture classification. Experimental results are presented to demonstrate the efficiency of the proposed method.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
023-0232006-1662 - Računalni vid u identifikaciji kinematike sportskih aktivnosti (Papić, Vladan, MZOS ) ( CroRIS)
177-0232006-1662 - Računalni vid u identifikaciji kinematike sportskih aktivnosti
Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split