Method and apparatus for object recognition using probability models
First Claim
1. A method for automatically recognizing or verifying objects in a digital image, said method comprising:
- accessing digital image data containing an object of interest therein;
detecting an object of interest in said digital image data;
normalizing said object of interest to generate a normalized object representation;
extracting a plurality of features from said normalized object representation; and
applying each extracted feature to a previously-determined additive probability model to determine the likelihood that the object of interest belongs to an existing class.
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Abstract
A method and an apparatus automatically recognize or verify objects in a digital image using probability models. According to a first aspect, a method and apparatus automatically recognize or verify objects in a digital image by: accessing digital image data including an object of interest therein; detecting an object of interest in the image; normalizing the object to generate a normalized object representation; extracting a plurality of features from the normalized object representation; and applying each feature to a previously-determined additive probability model to determine the likelihood that the object of interest belongs to an existing class. In one embodiment, the previously-determined additive probability model is an Additive Gaussian Model.
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Citations
32 Claims
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1. A method for automatically recognizing or verifying objects in a digital image, said method comprising:
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accessing digital image data containing an object of interest therein;
detecting an object of interest in said digital image data;
normalizing said object of interest to generate a normalized object representation;
extracting a plurality of features from said normalized object representation; and
applying each extracted feature to a previously-determined additive probability model to determine the likelihood that the object of interest belongs to an existing class. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. An apparatus for automatically recognizing or verifying objects in a digital image, said apparatus comprising:
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a digital image data input for accessing digital image data containing an object of interest therein;
an object detector for detecting an object of interest in said digital image data;
a normalizing unit for normalizing said object of interest to generate a normalized object representation;
a feature extracting unit for extracting a plurality of features from said normalized object representation; and
a likelihood determining unit for applying each extracted feature to a previously-determined additive probability model to determine the likelihood that the object of interest belongs to an existing class. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32)
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Specification