PDE seminar by Prof. Xue-Cheng Tai (University of Bergen)
Convex relaxation, graph cut and continuous max-flow algorithms for image processing and computer vision.
In this talk, we present a new global optimization based approach to contour evolution, with or without the novel variational shape constraint that imposes a generic star shape using a continuous max-flow framework. In theory, the proposed continuous max-flow model provides a dual perspective to the reduced continuous min-cut formulation of the contour evolution at each discrete time frame, which proves the global optimality of the discrete time contour propagation. In numerics, the proposed continuous max-flow formulations lead to efficient duality-based algorithms using modern convex optimization theories. Applications of the algorithms for image processing problems will be presented.
This talk is based in a joint work by: E. Bae, J. Yuan, Yuri Boykov and J. Liu.