Open Access
| Issue |
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|
|
|---|---|---|
| Article Number | 03001 | |
| Number of page(s) | 6 | |
| Section | Digital Signal and Image Processing | |
| DOI | https://doi.org/10.1051/matecconf/201817303001 | |
| Published online | 19 June 2018 | |
- D.G.Lowe,“Distinctive image features from scale-invariant keypoints,”International Journal of Computer Vision.Papers 60(2),91-110 (2004). [Google Scholar]
- L.Haomin,Z.Guofeng,and B.Hujun, “A survey of monocular simultaneous localization and mapping,” Journal of Computer-Aided Design and Computer Graphics. Papers 28(6),855-868 (2016). [Google Scholar]
- R. A. Newcombe et al.,“KinectFusion: Real-time dense surface mapping and tracking,”2011 10th IEEE International Symposium on Mixed and Augmented Reality, 127-136(2011). [CrossRef] [Google Scholar]
- H.Bay, A.Ess,T.Tuytelaars, L.Van Gool, “Speeded-Up Robust Features (SURF),”Computer Vision and Image Understanding.Papers 110(3),346-359 (2008). [CrossRef] [Google Scholar]
- Rublee, Ethan; Rabaud, Vincent; Konolige, Kurt; Bradski, “ORB: an ef fi cient alternative to SIFT or SURF,” IEEE International Conference on Computer Vision (ICCV),2564-2571(2011). [Google Scholar]
- M.Muja and D.G.Lowe,“Fast approximate nearest neighbors with automatic algorithm configuration,”VISAPP,331-340(2009). [Google Scholar]
- V.Lepetit,F.Moreno-Noguer,and P.Fua,“Epnp:An accurate o(n) solution to the pnp problem,”International Journal Computer Vision.Papers 81(2),155-166 (2008). [Google Scholar]
- Guo Yu,M.Bennamoun,F.Shoel,“3D object recognition in cluttered scenes with local surface features: a survey,”IEEE Transactions on Pattern Analysis and Machine Intelligence 36(11),2270-2287(2014). [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.