Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/107211
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electrical and Electronic Engineering | en_US |
dc.creator | Fu, CH | en_US |
dc.creator | Zhao, YW | en_US |
dc.creator | Zhang, HB | en_US |
dc.creator | Chan, YL | en_US |
dc.creator | Siu, WC | en_US |
dc.date.accessioned | 2024-06-13T01:04:36Z | - |
dc.date.available | 2024-06-13T01:04:36Z | - |
dc.identifier.isbn | 978-1-5090-2175-8 (Electronic) | en_US |
dc.identifier.isbn | 978-1-5090-2176-5 (Print on Demand(PoD)) | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/107211 | - |
dc.description | 2017 IEEE International Conference on Image Processing (ICIP), 17-20 September 2017, Beijing, China | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | ©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.rights | The following publication C. -H. Fu, Y. -W. Zhao, H. -B. Zhang, Y. -L. Chan and W. -C. Siu, "Depth modelling mode decision for depth intra coding via good feature," 2017 IEEE International Conference on Image Processing (ICIP), Beijing, China, 2017, pp. 4018-4022 is available at https://doi.org/10.1109/ICIP.2017.8297037. | en_US |
dc.subject | 3D-HEVC | en_US |
dc.subject | Corner point | en_US |
dc.subject | Depth map | en_US |
dc.subject | Intra prediction | en_US |
dc.subject | Multi-view video plus depth | en_US |
dc.title | Depth modelling mode decision for depth intra coding via good feature | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.spage | 4018 | en_US |
dc.identifier.epage | 4022 | en_US |
dc.identifier.doi | 10.1109/ICIP.2017.8297037 | en_US |
dcterms.abstract | The depth modelling modes (DMM) and 35 conventional intra modes (CHIMs) introduced in 3D-HEVC results in unacceptable huge complexity of depth intra coding. However, some redundancy between DMM and CHIMs could be avoided to accelerate the process. In this paper, a good feature-corner point (CP) is proposed to evaluate the orientation of edge in a given prediction unit (PU), by which a binary classifier is created. We further investigate the probability distribution of DMM, which is selected as the optimal intra mode in each category. According to the statistical analysis, the skipping of DMM decision is proposed to eliminate the cases which have been predicted well by CHIMs. The experimental results show that, compared with the test model HTM-13.0 of 3D-HEVC, the proposed algorithm can yield about 17% time reduction for depth intra coding with almost no degradation in coding performance. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | In Proceedings of 2017 IEEE International Conference on Image Processing (ICIP), 17-20 September 2017, Beijing, China, p. 4018-4022 | en_US |
dcterms.issued | 2017 | - |
dc.identifier.scopus | 2-s2.0-85045322543 | - |
dc.relation.conference | IEEE International Conference on Image Processing [ICIP] | en_US |
dc.description.validate | 202404 bckw | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | EIE-0575 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | Fundamental Research Funds for the Central Universities | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 9613885 | - |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Chan_Depth_Modelling_Mode.pdf | Pre-Published version | 524.17 kB | Adobe PDF | View/Open |
Page views
4
Citations as of Jun 30, 2024
SCOPUSTM
Citations
6
Citations as of Jun 21, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.