Learning structured prediction models for interactive image labeling
First Claim
1. An annotation system comprising:
- memory which stores;
a structured prediction model comprising a graphical structure which represents predicted correlations between values assumed by labels in a set of labels, the graphical structure comprising at least one tree structure, wherein in at least one of the tree structures, each of the labels in the set of labels is in exactly one node of the tree structure, the nodes of the tree having at most a predefined number k of the labels, and each of a plurality of the nodes has more than one of the labels, and edges between the nodes define those pairs of nodes for which predicted correlations between the values of pairs of their labels is used in the label prediction;
memory which stores instructions for;
generating feature-based predictions for values of labels in the set of labels based on features extracted from an image; and
predicting a value for at least one label from the set of labels for the image based on the feature-based label predictions, and the structured prediction model, and, when the instructions include instructions for receiving an assigned value for at least one label from the set of labels for the image, the predicted value being also based on an assigned value for at least one other label, if one has been assigned; and
a processor for executing the instructions.
7 Assignments
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Accused Products
Abstract
A system and a method are provided for labeling images and for generating an annotation system. The labeling method includes providing a graphical structure, such as a tree structure, which graphically represents predictive correlations between labels in a set of labels. The predictive correlations can, for example, estimate the likelihood, in a training set, that knowing one label has a given value, another label will have a given value. An image to be labeled is received. Feature-based predictions for values of labels in the set of labels are computed for the image. A value for at least one label for the image from the set of labels is computed based on the feature-based label predictions and inference on the structured prediction model.
41 Citations
27 Claims
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1. An annotation system comprising:
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memory which stores; a structured prediction model comprising a graphical structure which represents predicted correlations between values assumed by labels in a set of labels, the graphical structure comprising at least one tree structure, wherein in at least one of the tree structures, each of the labels in the set of labels is in exactly one node of the tree structure, the nodes of the tree having at most a predefined number k of the labels, and each of a plurality of the nodes has more than one of the labels, and edges between the nodes define those pairs of nodes for which predicted correlations between the values of pairs of their labels is used in the label prediction; memory which stores instructions for; generating feature-based predictions for values of labels in the set of labels based on features extracted from an image; and predicting a value for at least one label from the set of labels for the image based on the feature-based label predictions, and the structured prediction model, and, when the instructions include instructions for receiving an assigned value for at least one label from the set of labels for the image, the predicted value being also based on an assigned value for at least one other label, if one has been assigned; and a processor for executing the instructions. - View Dependent Claims (2, 3, 4, 5, 9, 10, 11, 12, 25, 26, 27)
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6. An annotation system comprising:
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memory which stores; a structured prediction model which represents predicted correlations between values assumed by labels in a set of labels, the structured prediction model comprises at least one tree structure and wherein in at least one of the tree structures, each of the labels in the set of labels is in exactly one node of the tree and edges between the nodes define those pairs of nodes for which predicted correlations between the values of pairs of their labels is used in the label prediction; memory which stores instructions for; generating feature-based predictions for values of labels in the set of labels based on features extracted from an image; providing for receiving an assigned value for at least one label from the set of labels for the image, and predicting a value for at least one label from the set of labels for the image based on the feature-based label predictions, and the structured prediction model, the predicted value being also based on an assigned value for at least one other label, if one has been assigned, the system having a mode in which for an input image to be labeled, a plurality of the label values for the image are elicited from a user, and wherein the instructions for predicting the value for the at least one label for the input image are based on predictions using features extracted from the image which are modified by the predicted correlations of the tree structure which propagates modified predictions on values of the labels provided by the user to other labels via the edges; and a processor for executing the instructions. - View Dependent Claims (7, 8)
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13. A method for labeling images comprising:
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providing a structured prediction model in memory which represents predictive correlations between labels in a set of labels, the structured prediction model comprising a tree structure in which each of the labels in the set of labels is in exactly one node of the tree structure and edges between the nodes define pairs of nodes for which predicted correlations between values of pairs of labels is stored, the prediction of the value for the at least one label value being based on the predicted correlations; receiving an image to be labeled; eliciting a plurality of the label values for the image from a user; generating feature-based predictions for values of labels in the set of labels based on features extracted from the image; and with a processor, predicting a value for at least one label from the set of labels for the image based on the feature-based label predictions and predictive correlations of the structured prediction model, and based on an assigned label value for at least one other label, the assigned label value comprising the elicited label values, the prediction of the value for the at least one label for the input image including modifying at least one of the predicted correlations between values of the node which includes the label whose value has been elicited and at least those nodes linked by edges to that node based on the elicited value. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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Specification