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Posture recognition using sensing blocks
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Xi, Yulong | - |
| dc.contributor.author | Cho, Seoungjae | - |
| dc.contributor.author | Um, Kyhyun | - |
| dc.contributor.author | Cho, Kyungeun | - |
| dc.date.accessioned | 2024-09-26T15:02:26Z | - |
| dc.date.available | 2024-09-26T15:02:26Z | - |
| dc.date.issued | 2015-12 | - |
| dc.identifier.issn | 1876-1100 | - |
| dc.identifier.issn | 1876-1119 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/25606 | - |
| dc.description.abstract | Posture recognition has been investigated in a variety of fields including medicine, HCI, and video games. In particular, it is important to improve the generality and recognition speed of posture recognition to improve the user experience in diverse kinds of user environments. This paper proposes a posture recognition algorithm with high generality and recognition speed. The algorithm is able to recognize a variety of postures, regardless of the number of joints recognized in human skeleton data. Furthermore, experimental results show that the method can quickly process a large quantity of data and recognize 22 postures in real time. © Springer Science+Business Media Singapore 2015. | - |
| dc.format.extent | 5 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | Springer Verlag | - |
| dc.title | Posture recognition using sensing blocks | - |
| dc.type | Article | - |
| dc.publisher.location | 독일 | - |
| dc.identifier.doi | 10.1007/978-981-10-0281-6_35 | - |
| dc.identifier.scopusid | 2-s2.0-84951271378 | - |
| dc.identifier.bibliographicCitation | Lecture Notes in Electrical Engineering, v.373, pp 243 - 247 | - |
| dc.citation.title | Lecture Notes in Electrical Engineering | - |
| dc.citation.volume | 373 | - |
| dc.citation.startPage | 243 | - |
| dc.citation.endPage | 247 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.subject.keywordAuthor | Human-computer interface | - |
| dc.subject.keywordAuthor | Pattern recognition | - |
| dc.subject.keywordAuthor | Posture recognition | - |
| dc.subject.keywordAuthor | Support vector machine | - |
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Related Researcher
- Cho, Kyung Eun
- College of Advanced Convergence Engineering (Department of Computer Science and Artificial Intelligence)