Dynamic Gesture Recognition and its Application to Sign Language

Franco Ronchetti

doi:10.24215/16666038.17.e21

Authors

Franco Ronchetti Institute of Research in Computer Science - School of Computer Science - University of La Plata, Argentina

DOI:

https://doi.org/10.24215/16666038.17.e21

Keywords:

automatic recognition

Abstract

The automatic recognition of human gestures is a complex multidisciplinary problem that has not yet been completely solved. Since the advent of digital video capture technologies, there have been attempts to recognize dynamic gestures for different purposes. In the recent years, new technologies such as depth sensors or highresolution cameras were incorporated as well as the high processing capacity of the current devices emerged, allowing the new technologies development capable of detecting different movements and acting in real time. Unlike the recognition of the spoken voice, which has been researched for more than forty years, the topic of this thesis is relatively new in the scientific area and it evolves rapidly as new devices appear as well as new computer vision algorithms.

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References

[1] F. Ronchetti, F. Quiroga, C. Estrebou, L. Lanzarini, A. Rosete. “Sign Language Recognition without frame-sequencing constraints: A proof of concept on the Argentinian Sign Language”. Advances in Artificial Intelligence - IBERAMIA 2016: 15th Ibero-American Conference on AI, San José, Costa Rica, November 2325, 2016, Proceedings. pp 338-349. Springer International Publishing. 2016.
[2] F. Ronchetti, F. Quiroga, C. Estrebou, L. Lanzarini, A. Rosete. “LSA64: An Argentinian Sign Language
Dataset”. XXII Congreso Argentino de Ciencias de la Computación. CACIC 2016. San Luis. Argentina. pp 794-803. October 2016.
[3] F. Ronchetti, F. Quiroga, C. Estrebou, L. Lanzarini. “Handshape recognition for Argentinian Sign Language using ProbSom”. Journal of Computer Science & Technology. ISSN 1666-6038. ISTEC – RedUNCI. Vol. 16, Num. 1, pp 01-05. April 2016.
[4] F. Ronchetti, F. Quiroga, L. Lanzarini, C. Estrebou. “Distribution of Action Movements (DAM): A Descriptor for Human Action Recognition”. Frontiers of Computer Science. ISSN 2095-2236. Springer, Higher Education Press. v9. pp 956-965. December 2015.