118,564 research outputs found
Superpixels, Occlusion and Stereo
Graph-based energy minimization is now the state of the art in stereo matching methods. In spite of its outstanding performance, few efforts have been made to enhance its capability of occlusion handling. We propose an occlusion constraint, an iterative optimization strategy and a mechanism that proceeds on both the digital pixel level and the super pixel level. Our method explicitly handles occlusion in the framework of graph-based energy minimization. It is fast and outperforms previous methods especially in the matching accuracy of boundary areas
Adaptively Transforming Graph Matching
Recently, many graph matching methods that incorporate pairwise constraint
and that can be formulated as a quadratic assignment problem (QAP) have been
proposed. Although these methods demonstrate promising results for the graph
matching problem, they have high complexity in space or time. In this paper, we
introduce an adaptively transforming graph matching (ATGM) method from the
perspective of functional representation. More precisely, under a
transformation formulation, we aim to match two graphs by minimizing the
discrepancy between the original graph and the transformed graph. With a linear
representation map of the transformation, the pairwise edge attributes of
graphs are explicitly represented by unary node attributes, which enables us to
reduce the space and time complexity significantly. Due to an efficient
Frank-Wolfe method-based optimization strategy, we can handle graphs with
hundreds and thousands of nodes within an acceptable amount of time. Meanwhile,
because transformation map can preserve graph structures, a domain
adaptation-based strategy is proposed to remove the outliers. The experimental
results demonstrate that our proposed method outperforms the state-of-the-art
graph matching algorithms
Propagating Conjunctions of AllDifferent Constraints
We study propagation algorithms for the conjunction of two AllDifferent
constraints. Solutions of an AllDifferent constraint can be seen as perfect
matchings on the variable/value bipartite graph. Therefore, we investigate the
problem of finding simultaneous bipartite matchings. We present an extension of
the famous Hall theorem which characterizes when simultaneous bipartite
matchings exists. Unfortunately, finding such matchings is NP-hard in general.
However, we prove a surprising result that finding a simultaneous matching on a
convex bipartite graph takes just polynomial time. Based on this theoretical
result, we provide the first polynomial time bound consistency algorithm for
the conjunction of two AllDifferent constraints. We identify a pathological
problem on which this propagator is exponentially faster compared to existing
propagators. Our experiments show that this new propagator can offer
significant benefits over existing methods.Comment: AAAI 2010, Proceedings of the Twenty-Fourth AAAI Conference on
Artificial Intelligenc
- …