Edge-Network-Assisted Real-Time Object Detection Framework for Autonomous Driving
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, S.-W. | - |
dc.contributor.author | Ko, K. | - |
dc.contributor.author | Ko, H. | - |
dc.contributor.author | Leung, V.C.M. | - |
dc.date.accessioned | 2021-12-04T21:00:05Z | - |
dc.date.available | 2021-12-04T21:00:05Z | - |
dc.date.created | 2021-08-31 | - |
dc.date.issued | 2021-01 | - |
dc.identifier.issn | 0890-8044 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/129445 | - |
dc.description.abstract | Computer vision tasks such as object detection are crucial for the operations of autonomous vehicles (AVs). Results of many tasks, even those requiring high computational power, can be obtained within a short delay by offloading them to edge clouds. However, although edge clouds are exploited, real-time object detection cannot always be guaranteed due to dynamic channel quality. To mitigate this problem, we propose an edge-network-assisted real-time object detection framework (EODF). In an EODF, AVs extract the region of interest (Rols) of the captured image when the channel quality is not sufficiently good for supporting real-time object detection. Then AVs compress the image data on the basis of the Rols and transmit the compressed one to the edge cloud. In so doing, real-time object detection can be achieved due to the reduced transmission latency. To verify the feasibility of our framework, we evaluate the probability that the results of object detection are not received within the inter-frame duration (i.e., outage probability) and their accuracy. From the evaluation, we demonstrate that the proposed EODF provides the results to AVs in real time and achieves satisfactory accuracy. © 1986-2012 IEEE. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.subject | Autonomous vehicles | - |
dc.subject | Image segmentation | - |
dc.subject | Object recognition | - |
dc.subject | Autonomous driving | - |
dc.subject | Channel quality | - |
dc.subject | Computational power | - |
dc.subject | Detection framework | - |
dc.subject | Dynamic channels | - |
dc.subject | EDGE Networks | - |
dc.subject | Outage probability | - |
dc.subject | Region of interest | - |
dc.subject | Object detection | - |
dc.title | Edge-Network-Assisted Real-Time Object Detection Framework for Autonomous Driving | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ko, H. | - |
dc.identifier.doi | 10.1109/MNET.011.2000248 | - |
dc.identifier.scopusid | 2-s2.0-85101065937 | - |
dc.identifier.wosid | 000641159800027 | - |
dc.identifier.bibliographicCitation | IEEE Network, v.35, no.1, pp.177 - 183 | - |
dc.relation.isPartOf | IEEE Network | - |
dc.citation.title | IEEE Network | - |
dc.citation.volume | 35 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 177 | - |
dc.citation.endPage | 183 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Hardware & Architecture | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordPlus | Autonomous vehicles | - |
dc.subject.keywordPlus | Image segmentation | - |
dc.subject.keywordPlus | Object recognition | - |
dc.subject.keywordPlus | Autonomous driving | - |
dc.subject.keywordPlus | Channel quality | - |
dc.subject.keywordPlus | Computational power | - |
dc.subject.keywordPlus | Detection framework | - |
dc.subject.keywordPlus | Dynamic channels | - |
dc.subject.keywordPlus | EDGE Networks | - |
dc.subject.keywordPlus | Outage probability | - |
dc.subject.keywordPlus | Region of interest | - |
dc.subject.keywordPlus | Object detection | - |
dc.subject.keywordAuthor | Image coding | - |
dc.subject.keywordAuthor | Image edge detection | - |
dc.subject.keywordAuthor | Object detection | - |
dc.subject.keywordAuthor | Real-time systems | - |
dc.subject.keywordAuthor | Task analysis | - |
dc.subject.keywordAuthor | Vehicle dynamics | - |
dc.subject.keywordAuthor | Autonomous vehicles | - |
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