Open Access
Issue
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
DOI https://doi.org/10.1051/itmconf/20171204012
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. [CrossRef] [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]

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