Cited 7 time in
Hand gesture detection and tracking methods based on background subtraction
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Song, W. | - |
| dc.contributor.author | Lu, Z. | - |
| dc.contributor.author | Li, J. | - |
| dc.contributor.author | Li, J. | - |
| dc.contributor.author | Liao, J. | - |
| dc.contributor.author | Cho, K. | - |
| dc.contributor.author | Um, K. | - |
| dc.date.accessioned | 2024-08-08T04:01:27Z | - |
| dc.date.available | 2024-08-08T04:01:27Z | - |
| dc.date.issued | 2014 | - |
| dc.identifier.issn | 1876-1100 | - |
| dc.identifier.issn | 1876-1119 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/17629 | - |
| dc.description.abstract | This paper combines the background subtraction and frame difference methods to detect a moving-hand area. Currently, hand-gesture recognition contains the following parts: hand area detection, hand tracking, and recognition. In this paper, we describe the moving-hand area detection and tracking parts of our work. First, we constructed a background image model that did not contain a moving hand. Then, using a background updating algorithm to obtain the authentic background image, we obtained the moving-hand area by subtracting the current image frame from the background image frame. We utilized a novel dynamic threshold method to enhance detection. We used the Microsoft Kinect to track the hand region because Kinect can capture information about the human body and the position of various body parts. The experiments demonstrated that our methods can be used to detect a moving region from an original image. © 2014 Springer-Verlag Berlin Heidelberg. | - |
| dc.format.extent | 6 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | Springer Verlag | - |
| dc.title | Hand gesture detection and tracking methods based on background subtraction | - |
| dc.type | Article | - |
| dc.publisher.location | 독일 | - |
| dc.identifier.doi | 10.1007/978-3-642-55038-6_76 | - |
| dc.identifier.scopusid | 2-s2.0-84902377742 | - |
| dc.identifier.bibliographicCitation | Lecture Notes in Electrical Engineering, v.309 LNEE, pp 485 - 490 | - |
| dc.citation.title | Lecture Notes in Electrical Engineering | - |
| dc.citation.volume | 309 LNEE | - |
| dc.citation.startPage | 485 | - |
| dc.citation.endPage | 490 | - |
| dc.type.docType | Conference Paper | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.subject.keywordAuthor | Background subtraction | - |
| dc.subject.keywordAuthor | Background updating methods | - |
| dc.subject.keywordAuthor | Dynamic threshold | - |
| dc.subject.keywordAuthor | Kinect | - |
| dc.subject.keywordAuthor | Skeleton information | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
30, Pildong-ro 1-gil, Jung-gu, Seoul, 04620, Republic of Korea+82-2-2260-3114
Copyright(c) 2023 DONGGUK UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
