Open Access
ITM Web Conf.
Volume 12, 2017
The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
Article Number 04012
Number of page(s) 5
Section Session 4: Information Theory and Information Systems
Published online 05 September 2017
  1. Noma T, Zhao L, Badler N I. Design of a Virtual Human Presenter[J]. Computer Graphics & Applications IEEE, 2000, 20(4):79–85. [CrossRef] [EDP Sciences] [Google Scholar]
  2. Nijholt A, Welbergen V H, Zwiers J, et al. Introducing an Embodied Augmented Virtual Presenter Agent in a Virtual Meeting Room[J]. Acta Press, 2005. [Google Scholar]
  3. Trinh H, Ring L, Bickmore T. Dynamic Duo: Co-presenting with Virtual Agents[J]. 2015:1739–1748. [Google Scholar]
  4. Chuang Y Y, Curless B, Salesin D H, et al. A Bayesian approach to digital matting[C]// Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on. IEEE, 2001:II-264-II-271 vol.2. [Google Scholar]
  5. Jian S, Jia J, Tang C K, et al. Poisson Matting[J]. Acm Transactions on Graphics, 2004. [Google Scholar]
  6. Levin A, Lischinski D, Weiss Y. A Closed-Form Solution to Natural Image Matting[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2008, 30(2):228–242. [CrossRef] [Google Scholar]
  7. Wang J, Cohen M F. Optimized Color Sampling for Robust Matting[C]// Computer Vision and Pattern Recognition, 2007. CVPR ‘07. IEEE Conference on. IEEE, 2007:1–8. [Google Scholar]
  8. Liu W, Anguelov D, Erhan D, et al. SSD: Single Shot MultiBox Detector[J]. 2015. [Google Scholar]
  9. Girshick R, Donahue J, Darrell T, et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation[C]// Computer Vision and Pattern Recognition. IEEE, 2013:580–587. [Google Scholar]
  10. Ren S, He K, Girshick R, et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2015:1–1. [Google Scholar]
  11. Rother C, Kolmogorov V, Blake A. “GrabCut”[J]. Acm Transactions on Graphics, 2004, 23(3):309. [CrossRef] [Google Scholar]
  12. Ju W, Xiang D, Zhang B, et al. Random Walk and Graph Cut for Co-Segmentation of Lung Tumor on PET-CT Images.[J]. IEEE Transactions on Image Processing, 2015, 25(3):1192–1192. [CrossRef] [MathSciNet] [Google Scholar]
  13. Dong X, Shen J, Shao L, et al. Sub-Markov Random Walk for Image Segmentation[J]. IEEE Transactions on Image Processing, 2016, 25(2):516. [CrossRef] [MathSciNet] [Google Scholar]
  14. Chefd’Hotel C, Sebbane A. Random Walk and Front Propagation on Watershed Adjacency Graphs for Multilabel Image Segmentation[C]// IEEE, International Conference on Computer Vision. IEEE, 2007:1–7. [Google Scholar]
  15. Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2017, 39(4):640–651. [Google Scholar]
  16. Chen L C, Papandreou G, Kokkinos I, et al. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs[J]. 2016. [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.