Material recognition from an image
AssigneeMicrosoft Corporation
InventorCe LIU
Life of this patent
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Abstract
A method of operating a computer system to perform material recognition based on multiple features extracted from an image is described. A combination of low-level features extracted directly from the image and multiple novel mid-level features extracted from transformed versions of the image are selected and used to assign a material category to a single image. The novel mid-level features include non-reflectance based features such as the micro-texture features micro-jet and micro-SIFT and the shape feature curvature, and reflectance-based features including edge slice and edge ribbon. An augmented Latent Dirichlet Allocation (LDA) model is provided as an exemplary Bayesian framework for selecting a subset of features useful for material recognition of objects in an image.
Claims16
1-17. (canceled)
A computer system comprising:
- a processing device, and
- a memory device storing computer-executable instructions which, when executed by the processing device, cause the processing device to:
- extract a plurality of features from a plurality of images assigned to a plurality of material categories, wherein the plurality of features comprises at least one reflectance-based feature and at least one non-reflectance based feature;
- and
- select a subset of the plurality of features, wherein the subset of the plurality of features is selected by a learning procedure in which combinations of features are analyzed to determine the subset of the plurality of features,
- wherein the learning procedure is a greedy algorithm that considers contributions of each of the plurality of features in a stepwise manner.
23-25. (canceled)
A method implemented by one or more computer processing devices, the method comprising:
- receiving a training set of images assigned to multiple material categories;
- extracting multiple features from the training set of images;
- and
- analyzing combinations of the multiple features using a learning procedure to select a subset of the multiple features,
- wherein the learning procedure is a greedy algorithm that considers contributions of individual features of the multiple features one at a time.
31-32. (canceled)
A computer-readable storage medium storing computer readable instructions that, when executed by one or more processing devices, cause the one or more processing devices to perform acts comprising:
- receiving a set of images assigned to multiple material categories, the images of the set having multiple image features;
- dividing the set of images into a training set and an evaluation set;
- joining individual dictionaries of the multiple image features to create a combined dictionary;
- using the combined dictionary to train a recognition model on the training set to obtain a trained recognition model;
- and
- determining a material recognition rate for the trained recognition model based on recognition of individual material categories in the evaluation set by the trained recognition model.
(canceled)
Dependencies are inferred from the claim text.