Fast approximate energy minimization via graph cuts

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Fast approximate energy minimization via graph cuts (2001)

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by Yuri Boykov , Olga Veksler , Ramin Zabih

Venue:	IEEE Transactions on Pattern Analysis and Machine Intelligence
Citations:	2120 - 61 self

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@ARTICLE{Boykov01fastapproximate,
    author = {Yuri Boykov and Olga Veksler and Ramin Zabih},
    title = {Fast approximate energy minimization via graph cuts},
    journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
    year = {2001},
    volume = {23},
    pages = {2001}
}

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Abstract

In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function’s smoothness term must only involve pairs of pixels. We propose two algorithms that use graph cuts to compute a local minimum even when very large moves are allowed. The first move we consider is an α-βswap: for a pair of labels α, β, this move exchanges the labels between an arbitrary set of pixels labeled α and another arbitrary set labeled β. Our first algorithm generates a labeling such that there is no swap move that decreases the energy. The second move we consider is an α-expansion: for a label α, this move assigns an arbitrary set of pixels the label α. Our second

Keyphrases

graph cut fast approximate energy minimization arbitrary set energy function second move swap move early vision smoothness term first move local minimum large move major restriction first algorithm large class move exchange

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