L1-Optimized AAM Alignment
First Claim
Patent Images
1. An Active Appearance Model machine, comprising:
- a learn module providing a model image of a class of object, said model image being created by combining feature information from an image library of true image samples of said class of object, said learn module further providing a statistical model fitting function defining shape and appearance features of said class of object;
an input for receiving an input image; and
an align module optimizing said statistical model fitting function to determine a best fit of said model image and said input image through iterative applications of said statistical model fitting function to produce an aligned image;
wherein in each of said iterative applications, a shape parameter coefficient p and an appearance parameter coefficient λ
within said statistical model fitting function are updated by L1 minimization, and said L1 minimization being defined as;
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Abstract
An Active Appearance Model, AAM, uses an L1 minimization-based approach to aligning an input test image. In each iterative application of its statistical model fitting function, a shape parameter coefficient p and an appearance parameter coefficient λ within the statistical model fitting function are updated by L1 minimization. The AAM further includes a canonical classifier to determine if an aligned image is a true example of the class of object being sought before the AAM is permitted to output its aligned image.
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Citations
25 Claims
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1. An Active Appearance Model machine, comprising:
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a learn module providing a model image of a class of object, said model image being created by combining feature information from an image library of true image samples of said class of object, said learn module further providing a statistical model fitting function defining shape and appearance features of said class of object; an input for receiving an input image; and an align module optimizing said statistical model fitting function to determine a best fit of said model image and said input image through iterative applications of said statistical model fitting function to produce an aligned image; wherein in each of said iterative applications, a shape parameter coefficient p and an appearance parameter coefficient λ
within said statistical model fitting function are updated by L1 minimization, and said L1 minimization being defined as; - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. An Active Appearance Model machine, comprising:
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a learn module providing a model image of a class of object, said model image being created by combining feature information from an image library of true image samples of said class of object, said learn module further providing a statistical model fitting function defining shape and appearance features of said class of object; an input for receiving an input image; an align module optimizing said statistical model fitting function to determine a best fit of said model image and said input image through iterative applications of said statistical model fitting function to produce an aligned image; canonical class classifier to determine if said aligned image is a true representation of said class of object; and an output for outputting said aligned image only if said canonical class classifier determines that said aligned image is a true representation of said class of object. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
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Specification