Solving multilabel MRFs using incremental α-expansion on the GPUs

Authors:
Vibhav Vineet;P. J. Narayanan
Affiliations:
Center for Visual Information Technology, International Institute of Information Technology, Hyderabad, India;Center for Visual Information Technology, International Institute of Information Technology, Hyderabad, India
Venue:
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Year:
2009

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Abstract

Many vision problems map to the minimization of an energy function over a discrete MRF Fast performance is needed if the energy minimization is one step in a control loop In this paper, we present the incremental α-expansion algorithm for high-performance multilabel MRF optimization on the GPU Our algorithm utilizes the grid structure of the MRFs for good parallelism on the GPU We improve the basic push-relabel implementation of graph cuts using the atomic operations of the GPU and by processing blocks stochastically We also reuse the flow using reparametrization of the graph from cycle to cycle and iteration to iteration for fast performance We show results on various vision problems on standard datasets Our approach takes 950 milliseconds on the GPU for stereo correspondence on Tsukuba image with 16 labels compared to 5.4 seconds on the CPU.