Video-Based Point-Cloud-Compression Standard in MPEG: From Evidence Collection to Committee Draft
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jang, Euee S. | - |
dc.contributor.author | Preda, Marius | - |
dc.contributor.author | Mammou, Khaled | - |
dc.contributor.author | Tourapis, Alexis M. | - |
dc.contributor.author | Kim, Jungsun | - |
dc.contributor.author | Graziosi, Danillo B. | - |
dc.contributor.author | Rhyu, Sungryeul | - |
dc.contributor.author | Budagavi, Madhukar | - |
dc.date.accessioned | 2022-07-09T15:04:23Z | - |
dc.date.available | 2022-07-09T15:04:23Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2019-05 | - |
dc.identifier.issn | 1053-5888 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/147858 | - |
dc.description.abstract | The widespread adoption of new 3D sensor and authoring technologies has made it possible to capture 3D scenes and models in real time with decent visual quality. As an example, Microsoft's Kinect and Apple's PrimeSense technology are now being used in a wide variety of interactive 3D mobile applications, including gaming and augmented reality applications. The latest smartphones are equipped with multiple cameras, which can be readily used to generate depth images. Some of the latest smartphones also include depth-ranging sensors that can be used for 3D model generation. Light-based detection and ranging (lidar) technologies are yet another field where 3D depth acquisition is important. Realtime 3D scenery detection and ranging has become an important issue for the emerging field of autonomous navigation and driving applications. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Video-Based Point-Cloud-Compression Standard in MPEG: From Evidence Collection to Committee Draft | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jang, Euee S. | - |
dc.identifier.doi | 10.1109/MSP.2019.2900721 | - |
dc.identifier.scopusid | 2-s2.0-85065066187 | - |
dc.identifier.wosid | 000466554100011 | - |
dc.identifier.bibliographicCitation | IEEE SIGNAL PROCESSING MAGAZINE, v.36, no.3, pp.118 - 123 | - |
dc.relation.isPartOf | IEEE SIGNAL PROCESSING MAGAZINE | - |
dc.citation.title | IEEE SIGNAL PROCESSING MAGAZINE | - |
dc.citation.volume | 36 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 118 | - |
dc.citation.endPage | 123 | - |
dc.type.rims | ART | - |
dc.type.docType | Editorial Material | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | Augmented reality | - |
dc.subject.keywordPlus | Motion Picture Experts Group standards | - |
dc.subject.keywordPlus | Optical radar | - |
dc.subject.keywordPlus | Smartphones | - |
dc.subject.keywordPlus | Augmented reality applications | - |
dc.subject.keywordPlus | Autonomous navigation | - |
dc.subject.keywordPlus | Compression standards | - |
dc.subject.keywordPlus | Evidence collection | - |
dc.subject.keywordPlus | Microsoft&apos | - |
dc.subject.keywordPlus | s kinect | - |
dc.subject.keywordPlus | Mobile applications | - |
dc.subject.keywordPlus | Multiple cameras | - |
dc.subject.keywordPlus | Visual qualities | - |
dc.subject.keywordPlus | 3D modeling | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/8700674 | - |
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