Generic visual classification with gradient components-based dimensionality enhancement
First Claim
1. A method for classifying an image, the method comprising:
- extracting model fitting data for the image respective to a generative model that includes parameters relating to visual words of at least an image class-specific visual vocabulary;
computing a higher-dimensionality representation of the model fitting data that includes at least some components of a gradient of the model fitting data in a vector space defined by the parameters of the generative model;
repeating the extracting and computing for a plurality of generative models each having at least a different image class-specific vocabulary corresponding to a different class of images; and
classifying the image based on the higher-dimensionality representations.
6 Assignments
0 Petitions
Accused Products
Abstract
In an image classification system (70), a plurality of generative models (30) correspond to a plurality of image classes. Each generative model embodies a merger of a general visual vocabulary and an image class-specific visual vocabulary. A gradient-based class similarity modeler (40) includes (i) a model fitting data extractor (46) that generates model fitting data of an image (72) respective to each generative model and (ii) a dimensionality enhancer (50) that computes a gradient-based vector representation of the model fitting data with respect to each generative model in a vector space defined by the generative model. An image classifier (76) classifies the image respective to the plurality of image classes based on the gradient-based vector representations of class similarity.
-
Citations
20 Claims
-
1. A method for classifying an image, the method comprising:
-
extracting model fitting data for the image respective to a generative model that includes parameters relating to visual words of at least an image class-specific visual vocabulary;
computing a higher-dimensionality representation of the model fitting data that includes at least some components of a gradient of the model fitting data in a vector space defined by the parameters of the generative model;
repeating the extracting and computing for a plurality of generative models each having at least a different image class-specific vocabulary corresponding to a different class of images; and
classifying the image based on the higher-dimensionality representations. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
-
-
12. An image classification system comprising:
-
a plurality of generative models corresponding to a plurality of image classes, each generative model embodying at least an image class-specific visual vocabulary;
a gradient-based class similarity modeler including (i) a model fitting data extractor that generates model fitting data of an image respective to each generative model and (ii) a dimensionality enhancer that computes a gradient-based vector representation of the model fitting data with respect to each generative model in a vector space defined by the generative model; and
an image classifier that classifies the image respective to the plurality of image classes based on the gradient-based vector representations. - View Dependent Claims (13, 14, 15)
-
-
16. A method for classifying an image, the method comprising:
-
extracting model fitting data for the image respective to a generative model embodying a merger of a general visual vocabulary and an image class-specific visual vocabulary;
increasing a dimensionality of the model fitting data by computing derivatives of the model fitting data in a vector space defined by parameters of the generative model;
repeating the extracting and increasing for a plurality of generative models each embodying a merger of the general visual vocabulary and a different image class-specific vocabulary for a different image class; and
classifying the image based on the increased-dimensionality model fitting data. - View Dependent Claims (17, 18, 19, 20)
-
Specification