Method of performing shape localization
AssigneeThe Board of Trustees of the University of Illinois
InventorsJilin Tu, Thomas S. Huang
Life of this patent
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Abstract
A method for performing shape localization in an image includes deriving a model shape from a database of a plurality of sample shapes. The model shape is defined by a set of landmarks. The method further includes deriving a texture likelihood model of present sub-patches of the set of landmarks defining the model shape in the image, and proposing a new set of landmarks that approximates a true location of features of the shape based on a sample proposal model of the present sub-patches. A CONDENSATION algorithm is used to derive the texture likelihood model and the proposed new set of landmarks.
Claims26
A method for performing face shape localization in an image, comprising:
- deriving a model face shape from a database of a plurality of sample face shapes, said model face shape being defined by a set of landmarks;
- deriving a texture likelihood model of present sub-patches of said set of landmarks defining said model face shape in the image;
- and
- proposing a new set of landmarks that approximates a true location of features of the face shape based on a sample proposal model of said present sub-patches;
- wherein said deriving said texture likelihood model and said proposing said new set of landmarks are conducted using a CONDENSATION algorithm;
- and
- said model face shape is derived from a prior probabilistic distribution of a predefined model p(m),
- said texture likelihood model of said present sub-patches is derived from a local texture likelihood distribution model p(I|m), and
- said sample proposal model is derived based on a texture likelihood model of subsequent sub-patches of a set of landmarks in the image at proposed locations in a vicinity of said present sub-patches of said present set of landmarks.
Method for performing a face localization in an image based on a Bayesian rule, comprising:
- deriving a predefined face shape model m;
- employing conditional density propagation (CONDENSATION) algorithm to locate a face shape in the image using a prior probabilistic distribution of a model p(m) based on said predefined face shape model m, and a local texture likelihood distribution given said predefined face shape model with specific model parameters p(I|m).
Dependencies are inferred from the claim text.