An open-source platform for human pose estimation and tracking using a heterogeneous multi-sensor system
DC Field | Value | Language |
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dc.contributor.author | Patil, A.K. | - |
dc.contributor.author | Balasubramanyam, A. | - |
dc.contributor.author | Ryu, J.Y. | - |
dc.contributor.author | Chakravarthi, B. | - |
dc.contributor.author | Chai, Y.H. | - |
dc.date.accessioned | 2021-07-21T03:42:22Z | - |
dc.date.available | 2021-07-21T03:42:22Z | - |
dc.date.issued | 2021-04 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.issn | 1424-3210 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/47711 | - |
dc.description.abstract | Human pose estimation and tracking in real-time from multi-sensor systems is essential for many applications. Combining multiple heterogeneous sensors increases opportunities to improve human motion tracking. Using only a single sensor type, e.g., inertial sensors, human pose estimation accuracy is affected by sensor drift over longer periods. This paper proposes a human motion tracking system using lidar and inertial sensors to estimate 3D human pose in real-time. Human motion tracking includes human detection and estimation of height, skeletal parameters, position, and orientation by fusing lidar and inertial sensor data. Finally, the estimated data are reconstructed on a virtual 3D avatar. The proposed human pose tracking system was developed using open-source platform APIs. Experimental results verified the proposed human position tracking accuracy in real-time and were in good agreement with current multi-sensor systems. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | MDPI AG | - |
dc.title | An open-source platform for human pose estimation and tracking using a heterogeneous multi-sensor system | - |
dc.type | Article | - |
dc.identifier.doi | 10.3390/s21072340 | - |
dc.identifier.bibliographicCitation | Sensors, v.21, no.7 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.wosid | 000638874900001 | - |
dc.identifier.scopusid | 2-s2.0-85103032574 | - |
dc.citation.number | 7 | - |
dc.citation.title | Sensors | - |
dc.citation.volume | 21 | - |
dc.type.docType | Article | - |
dc.publisher.location | 스위스 | - |
dc.subject.keywordAuthor | Detection | - |
dc.subject.keywordAuthor | Heterogeneous sensor | - |
dc.subject.keywordAuthor | Human pose estimation | - |
dc.subject.keywordAuthor | Inertial sensor | - |
dc.subject.keywordAuthor | Lidar sensor | - |
dc.subject.keywordAuthor | Multi-sensor | - |
dc.subject.keywordAuthor | Sensor fusion | - |
dc.subject.keywordAuthor | Tracking | - |
dc.subject.keywordPlus | Gesture recognition | - |
dc.subject.keywordPlus | Inertial navigation systems | - |
dc.subject.keywordPlus | Open systems | - |
dc.subject.keywordPlus | Optical radar | - |
dc.subject.keywordPlus | Real time systems | - |
dc.subject.keywordPlus | Three dimensional computer graphics | - |
dc.subject.keywordPlus | Tracking (position) | - |
dc.subject.keywordPlus | Heterogeneous sensors | - |
dc.subject.keywordPlus | Human detection | - |
dc.subject.keywordPlus | Human motion tracking | - |
dc.subject.keywordPlus | Human pose estimations | - |
dc.subject.keywordPlus | Human pose tracking | - |
dc.subject.keywordPlus | Inertial sensor | - |
dc.subject.keywordPlus | Multi-sensor systems | - |
dc.subject.keywordPlus | Open source platforms | - |
dc.subject.keywordPlus | Motion tracking | - |
dc.relation.journalResearchArea | Chemistry | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Instruments & Instrumentation | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Instruments & Instrumentation | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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