Patent ID: 9443314
Filing Date: 2016-09-13
CPC Classification: G06K,G06T

Claim Text:
1. A computer-implemented method for training a classification model for determining labels for an input image, the method comprising: receiving, by one or more processors, a plurality of labeled or partially labeled training images, wherein each labeled or partially labeled training image comprises at least one label associated with a pixel in the training image, the label indicating an object class from a plurality of possible object classes associated with the pixel; training, by the one or more processors, a global classification model to learn a global mapping between features of the training images and the labels; clustering, by the one or more processors, the plurality of labeled training images based on label-based descriptors into a plurality of clusters, the label-based descriptors representing label-based image features; training, by the one or more processors, a plurality of local classification models to learn a local mapping between features of the training images in each cluster and the labels of the training images in the cluster; and storing, by the one or more processors, the global classification model and the plurality of local classification models to a storage medium; wherein training the global classification model comprises: wherein determining the features of each training image comprises: