eprintid: 4480
rev_number: 9
eprint_status: archive
userid: 305
dir: disk0/00/00/44/80
datestamp: 2021-06-18 11:12:38
lastmod: 2021-06-18 11:12:38
status_changed: 2021-06-18 11:12:38
type: article
metadata_visibility: show
creators_name: Nguyen, Duc Thao
creators_name: Nguyen, Viet Anh
creators_name: Le, Thanh Ha
creators_name: Ngo, Thi Duyen
creators_id: ltha@vnu.edu.vn
creators_id: Duyennt@vnu.edu.vn
title: Robustify Hand Tracking by Fusing Generative and Discriminative Methods
ispublished: pub
subjects: IT
divisions: fac_fit
abstract: With the development of virtual reality (VR) technology and its applications in many fields, creating simulated hands in the virtual environment is an e ective way to replace the controller as well as to enhance user experience in interactive processes. Therefore, hand tracking problem is gaining a lot of research attention, making an important contribution in recognizing hand postures as well as tracking hand motions for VR’s input or human machine interaction applications. In order to create a markerless real-time hand tracking system suitable for natural human machine interaction, we propose a new method that combines generative and discriminative methods to solve the hand tracking problem using a single RGBD camera. Our system removes the requirement of the user having to wear to color wrist band and robustifies the hand localization even in di cult tracking scenarios.
date: 2021
date_type: published
publisher: VNU
full_text_status: none
publication: VNU Journal of Science: Computer Science and Communication Engineering
volume: 37
number: 1
refereed: FALSE
issn: 2588-1086
citation:   Nguyen, Duc Thao and Nguyen, Viet Anh and Le, Thanh Ha and Ngo, Thi Duyen  (2021) Robustify Hand Tracking by Fusing Generative and Discriminative Methods.  VNU Journal of Science: Computer Science and Communication Engineering, 37  (1).    ISSN 2588-1086