Patent Document ID: 8774515
Application ID: 13090378

Base 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.

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Claim 25:
25. A method for generating the annotation system of claim 1 , comprising: receiving a training set of manually-labeled training images; for each of the training images, for each of a set of labels, generating a feature function based on features extracted from the image which predicts a value of the label for the image; estimating mutual information between pairs of labels in a set of labels based on the training images; optionally, clustering the set of labels into groups having at most a predetermined number k of labels; and with a processor, based on the mutual information and feature functions, generating the structured prediction model represented by a tree structure in which nodes of the tree structure include a respective single one of the labels or group of the labels, the nodes being linked by edges, each edge representing predicted correlations between values of labels in the pair of nodes connected by the edge, whereby when an image to be labeled is received, the tree structure allows predictions on labels to be informed by the predicted correlations in the tree structure.