Belief propagation and affinity measures
First Claim
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1. A method implemented by one or more computing devices, the method comprising:
- arriving at one or more beliefs for a parent node that are to be used to solve a labeling problem for the parent node for image processing;
calculating an affinity measure of the parent node in comparison with a child node of the parent node, the affinity measure describing how similar the parent node and the child node are to each other, the parent node and child node being in different hierarchical levels; and
responsive to a determination that the affinity measure indicates that the parent node and the child node are different by at least a defined amount, using hierarchical belief propagation to solve a labeling problem for the child node for image processing that does not employ the one or more beliefs for the parent node.
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Abstract
Belief propagation and affinity measure techniques are described. In one or more implementations, beliefs may be formed to solve a labeling problem for a node, such as to perform image processing. An affinity measure may be calculated that describes how similar the node is to another node. This affinity measure may then be used as a basis to determine whether the share the belief formed for the node with the other node to solve a labeling problem for the other node.
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Citations
20 Claims
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1. A method implemented by one or more computing devices, the method comprising:
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arriving at one or more beliefs for a parent node that are to be used to solve a labeling problem for the parent node for image processing; calculating an affinity measure of the parent node in comparison with a child node of the parent node, the affinity measure describing how similar the parent node and the child node are to each other, the parent node and child node being in different hierarchical levels; and responsive to a determination that the affinity measure indicates that the parent node and the child node are different by at least a defined amount, using hierarchical belief propagation to solve a labeling problem for the child node for image processing that does not employ the one or more beliefs for the parent node. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. One or more non-transitory computer-readable storage media comprising instructions that are stored thereon that, responsive to execution by a computing device, causes the computing device to perform operations comprising:
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arriving at one or more beliefs for a node that are to be used as part of a labeling problem for the node; calculating an affinity measure of the node in comparison with at least one or more other nodes in a different hierarchical level, the affinity measure describing a similarity of the node to the one or more other nodes; and responsive to a determination that the affinity measure indicates that the similarity is within a pre-defined amount, using the one or more beliefs for the node as part of solving a labeling problem for the one or more other nodes. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A system comprising:
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one or more processors; one or more computer-readable storage media; at least one module implemented at least partially in hardware, the at least one module configured to arriving at one or more beliefs for a parent node that are to be used in hierarchical belief propagation to solve a labeling problem for pixels in the parent node; and one or more modules implemented at least partially in hardware, the one or more modules configured to; calculate an affinity measure of the parent node in comparison with a child node, the affinity measure describing how similar the parent node and the child node are to each other, the parent node and child node being in different hierarchical levels; responsive to a determination that the affinity measure indicates that the similarity is within a pre-defined amount, using hierarchical belief propagation to solve the labeling problem for one or more pixels in the child node using the one or more beliefs that were arrived at for the parent node; and responsive to a determination that the affinity measure indicates that the similarity is not within the pre-defined amount, using hierarchical belief propagation to solve the labeling problem for one or more pixels in the child node without using the one or more beliefs that were arrived at for the parent node. - View Dependent Claims (18, 19, 20)
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Specification