eprintid: 1544
rev_number: 8
eprint_status: archive
userid: 243
dir: disk0/00/00/15/44
datestamp: 2016-05-23 03:12:20
lastmod: 2016-05-23 03:12:52
status_changed: 2016-05-23 03:12:20
type: conference_item
metadata_visibility: show
creators_name: Pham, Quoc Thang
creators_name: Nguyen, Duc Dung
creators_name: Nguyen, Thanh Thuy
creators_id: nguyenthanhthuy@vnu.edu.vn
title: The vector machine learning methods on sign language recognition problem
ispublished: pub
subjects: IT
divisions: fac_fit
abstract: Human gesture recognition is a rather new field and many challenges, especial when motion capture devices become more popular. Sign language recognition is a concrete example of gesture recognition. Various studies have shown that the vector machine methods with Gaussian kernels are among the most prominent models for an accurate gesture classification. In this study, we present the application of vector machine learning methods to sign language recognition problem. We demonstrate that the vector machines (VMs) could also achieve the state-of-the-art predictive performance. The experimental results on the Auslan data set show the feasibility and effectiveness of these methods.
date: 2016-03-26
date_type: published
full_text_status: public
pres_type: poster
event_title: SW4PHD: the 2016 Scientific Workshop for PhD Students
event_location: Hanoi
event_dates: 26 March 2016
event_type: workshop
refereed: FALSE
citation:   Pham, Quoc Thang and Nguyen, Duc Dung and Nguyen, Thanh Thuy  (2016) The vector machine learning methods on sign language recognition problem.  In: SW4PHD: the 2016 Scientific Workshop for PhD Students, 26 March 2016, Hanoi.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1544/1/Poster%20%28English%29%20%28Pham%20Quoc%20Thang%29.pdf