Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Quang Nguyen | - |
dc.contributor.author | Yun, Sang-Seok | - |
dc.contributor.author | Choi, JongSuk | - |
dc.date.accessioned | 2024-01-19T11:38:18Z | - |
dc.date.available | 2024-01-19T11:38:18Z | - |
dc.date.created | 2022-03-07 | - |
dc.date.issued | 2016 | - |
dc.identifier.issn | 2325-033X | - |
dc.identifier.uri | https://pubs.kist.re.kr/handle/201004/114991 | - |
dc.description.abstract | This paper presents a perception sensor network (PSN) for detect audio-based emergency situations such as human scream. The PSN consists of multiple units, each has a Kinect and a pan-tilt-zoom camera. Audio signals, which are acquired by the Kinect microphone array, are used in sound source classification and sound source localization. In order to work in multi-person scenarios, we propose an audio-visual fusion method to detect a single speaking person among multiple ones. The PSN system was demonstrated in a scenario having four persons, where the system is able to detect and localize the screaming person and send a robot to that location to check his/her condition. | - |
dc.language | English | - |
dc.publisher | IEEE | - |
dc.title | Detection of Audio-based Emergency Situations using Perception Sensor Network | - |
dc.type | Conference | - |
dc.description.journalClass | 1 | - |
dc.identifier.bibliographicCitation | 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), pp.763 - 766 | - |
dc.citation.title | 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) | - |
dc.citation.startPage | 763 | - |
dc.citation.endPage | 766 | - |
dc.citation.conferencePlace | US | - |
dc.citation.conferencePlace | Xian, PEOPLES R CHINA | - |
dc.citation.conferenceDate | 2016-08-19 | - |
dc.relation.isPartOf | 2016 13TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAI) | - |
dc.identifier.wosid | 000387249900176 | - |
dc.identifier.scopusid | 2-s2.0-85000402149 | - |
dc.type.docType | Proceedings Paper | - |
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