A Combined Method of Skin-and Depth-based Hand Gesture Recognition
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sokhib, Tukhtaev | - |
dc.contributor.author | Whangbo, Taeg Keun | - |
dc.date.available | 2020-03-03T06:43:13Z | - |
dc.date.created | 2020-02-24 | - |
dc.date.issued | 2020-01 | - |
dc.identifier.issn | 1683-3198 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/17650 | - |
dc.description.abstract | Kinect is a promising acquisition device that provides useful information on a scene through color and depth data. There has been a keen interest in utilizing Kinect in many computer vision areas such as gesture recognition. Given the advantages that Kinect provides, hand gesture recognition can be deployed efficiently with minor drawbacks. This paper proposes a simple and yet efficient way of hand gesture recognition via segmenting a hand region from both color and depth data acquired by Kinect v1. The Inception model of the image recognition system is used to check the reliability of the proposed method. Experimental results are derived from a sample dataset of Microsoft Kinect hand acquisitions. Under the appropriate conditions, it is possible to achieve high accuracy in close to real time. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ZARKA PRIVATE UNIV | - |
dc.relation.isPartOf | INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY | - |
dc.subject | COLOR DETECTION | - |
dc.title | A Combined Method of Skin-and Depth-based Hand Gesture Recognition | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000504051200017 | - |
dc.identifier.doi | 10.34028/iajit/17/1/16 | - |
dc.identifier.bibliographicCitation | INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY, v.17, no.1, pp.137 - 145 | - |
dc.identifier.scopusid | 2-s2.0-85078286557 | - |
dc.citation.endPage | 145 | - |
dc.citation.startPage | 137 | - |
dc.citation.title | INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY | - |
dc.citation.volume | 17 | - |
dc.citation.number | 1 | - |
dc.contributor.affiliatedAuthor | Sokhib, Tukhtaev | - |
dc.contributor.affiliatedAuthor | Whangbo, Taeg Keun | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | Gesture recognition | - |
dc.subject.keywordAuthor | microsoft kinect | - |
dc.subject.keywordAuthor | inception model | - |
dc.subject.keywordAuthor | depth | - |
dc.subject.keywordPlus | COLOR DETECTION | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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