relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1544/
title: The vector machine learning methods on sign language recognition problem
creator: Pham, Quoc Thang
creator: Nguyen, Duc Dung
creator: Nguyen, Thanh Thuy
subject: Information Technology (IT)
description: 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
type: Conference or Workshop Item
type: NonPeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1544/1/Poster%20%28English%29%20%28Pham%20Quoc%20Thang%29.pdf
identifier:   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.