Y
Yuri Boykov
Researcher at University of Waterloo
Publications - 124
Citations - 32510
Yuri Boykov is an academic researcher from University of Waterloo. The author has contributed to research in topics: Image segmentation & Cut. The author has an hindex of 44, co-authored 124 publications receiving 29588 citations. Previous affiliations of Yuri Boykov include Carnegie Mellon University & University of Western Ontario.
Papers
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Journal ArticleDOI
Fast approximate energy minimization via graph cuts
TL;DR: This work presents two algorithms based on graph cuts that efficiently find a local minimum with respect to two types of large moves, namely expansion moves and swap moves that allow important cases of discontinuity preserving energies.
Journal ArticleDOI
An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision
Yuri Boykov,Vladimir Kolmogorov +1 more
TL;DR: This paper compares the running times of several standard algorithms, as well as a new algorithm that is recently developed that works several times faster than any of the other methods, making near real-time performance possible.
Proceedings ArticleDOI
Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images
Yuri Boykov,Marie-Pierre Jolly +1 more
TL;DR: In this paper, the user marks certain pixels as "object" or "background" to provide hard constraints for segmentation, and additional soft constraints incorporate both boundary and region information.
Proceedings ArticleDOI
Fast approximate energy minimization via graph cuts
TL;DR: This paper proposes two algorithms that use graph cuts to compute a local minimum even when very large moves are allowed, and generates a labeling such that there is no expansion move that decreases the energy.
Book ChapterDOI
An Experimental Comparison of Min-cut/Max-flow Algorithms for Energy Minimization in Vision
Yuri Boykov,Vladimir Kolmogorov +1 more
TL;DR: The goal of this paper is to provide an experimental comparison of the efficiency of min-cut/max flow algorithms for applications in vision, comparing the running times of several standard algorithms, as well as a new algorithm that is recently developed.