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Xin Yang
Active Matting
Xin Yang, Ke Xu, Shaozhe Chen, Shengfeng He, Baocai Yin Yin, Rynson Lau
Image matting is an ill-posed problem. It requires a user input trimap or some strokes to obtain an alpha matte of the foreground object. A fine user input is essential to obtain a good result, which is either time consuming or suitable for experienced users who know where to place the strokes. In this paper, we explore the intrinsic relationship between the user input and the matting algorithm to address the problem of where and when the user should provide the input. Our aim is to discover the most informative sequence of regions for user input in order to produce a good alpha matte with minimum labeling efforts.
Total Least Squares Regression in Input Sparsity Time
Huaian Diao, Zhao Song, David Woodruff, Xin Yang
Neural Information Processing Systems http://nips.cc/
Total Least Squares Regression in Input Sparsity Time
Huaian Diao, Zhao Song, David Woodruff, Xin Yang
In the total least squares problem, one is given an m n matrix A, and an m d matrix B, and one seeks to "correct" both A and B, obtaining matrices  and B, so that there exists an X satisfying the equation ÂX = B. Typically the problem is overconstrained, meaning that m max(n, d).
Active Matting
Xin Yang, Ke Xu, Shaozhe Chen, Shengfeng He, Baocai Yin Yin, Rynson Lau
Image matting is an ill-posed problem. It requires a user input trimap or some strokes to obtain an alpha matte of the foreground object. A fine user input is essential to obtain a good result, which is either time consuming or suitable for experienced users who know where to place the strokes. In this paper, we explore the intrinsic relationship between the user input and the matting algorithm to address the problem of where and when the user should provide the input. Our aim is to discover the most informative sequence of regions for user input in order to produce a good alpha matte with minimum labeling efforts.