Alpha‐numeric hand gesture recognition based on fusion of spatial feature modelling and temporal feature modelling.
Saved in:
| Title: | Alpha‐numeric hand gesture recognition based on fusion of spatial feature modelling and temporal feature modelling. |
|---|---|
| Authors: | Yang, C.1 (AUTHOR), Ku, B.1 (AUTHOR), Han, D.K.2 (AUTHOR), Ko, H.1 (AUTHOR) hsko@korea.ac.kr |
| Source: | Electronics Letters (Wiley-Blackwell). Sep2016, Vol. 52 Issue 18, p1679-1681. 3p. |
| Abstract: | Alpha‐numeric gesture refers to writing in air of alphabet and numeric characters. With prevalent usage of vision enabled smart devices, these gestures are considered as an alternative user interface. As each individual has a unique handwriting style, it has been observed that alpha‐numeric gesturing also exhibits different individualistic styles, posing a challenge to the vision based gesture recognition. In this Letter, a simple but effective method of modelling alpha‐numeric hand gestures by fusing temporal‐feature‐state modelling and total‐trajectory‐shape modelling is proposed. The proposed method employs a convolution neural network that represents total‐trajectory‐shapes, and combines it with conventional conditional random fields based temporal‐feature‐state modelling. The proposed algorithm is evaluated in public database of both alphabet and numeric hand gestures. Experimental results show a performance improvement of the proposed algorithm compared with the state‐of‐the art methods. [ABSTRACT FROM AUTHOR] |
| Copyright of Electronics Letters (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 148785277 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Alpha‐numeric hand gesture recognition based on fusion of spatial feature modelling and temporal feature modelling. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yang%2C+C%2E%22">Yang, C.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ku%2C+B%2E%22">Ku, B.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Han%2C+D%2EK%2E%22">Han, D.K.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ko%2C+H%2E%22">Ko, H.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hsko@korea.ac.kr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Electronics+Letters+%28Wiley-Blackwell%29%22">Electronics Letters (Wiley-Blackwell)</searchLink>. Sep2016, Vol. 52 Issue 18, p1679-1681. 3p. – Name: Abstract Label: Abstract Group: Ab Data: Alpha‐numeric gesture refers to writing in air of alphabet and numeric characters. With prevalent usage of vision enabled smart devices, these gestures are considered as an alternative user interface. As each individual has a unique handwriting style, it has been observed that alpha‐numeric gesturing also exhibits different individualistic styles, posing a challenge to the vision based gesture recognition. In this Letter, a simple but effective method of modelling alpha‐numeric hand gestures by fusing temporal‐feature‐state modelling and total‐trajectory‐shape modelling is proposed. The proposed method employs a convolution neural network that represents total‐trajectory‐shapes, and combines it with conventional conditional random fields based temporal‐feature‐state modelling. The proposed algorithm is evaluated in public database of both alphabet and numeric hand gestures. Experimental results show a performance improvement of the proposed algorithm compared with the state‐of‐the art methods. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Electronics Letters (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=148785277 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1049/el.2016.0841 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 3 StartPage: 1679 Titles: – TitleFull: Alpha‐numeric hand gesture recognition based on fusion of spatial feature modelling and temporal feature modelling. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yang, C. – PersonEntity: Name: NameFull: Ku, B. – PersonEntity: Name: NameFull: Han, D.K. – PersonEntity: Name: NameFull: Ko, H. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2016 Type: published Y: 2016 Identifiers: – Type: issn-print Value: 00135194 Numbering: – Type: volume Value: 52 – Type: issue Value: 18 Titles: – TitleFull: Electronics Letters (Wiley-Blackwell) Type: main |
| ResultId | 1 |
