System and method for estimating the orientation of an object
First Claim
1. A method for estimating the orientation of an object comprising:
- providing a trained model of the object as training data, wherein the trained model of the object is produced by extracting unique features of the training data, projecting the features of the training data onto corresponding points of a model and determining a probability density function estimation for each model point;
extracting unique features of an image representing the object;
back projecting the features of the image onto points of the trained model; and
determining an estimated orientation of the object that most likely generates the features extracted from object.
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Abstract
The present invention is embodied in a system and method for automatically estimating the orientation or pose of an object, such as a human head, from any viewpoint and includes training and pose estimation modules. The training module uses known head poses for generating observations of the different types of head poses and the pose estimation module receives actual head poses of a subject and uses the training observations to estimate the actual head pose. Namely, the training module receives training data and extracts unique features of the data, projects the features onto corresponding points of a model and determines a probability density function estimation for each model point to produce a trained model. The pose estimation module receives the trained model and an input object and extracts unique input features of the input object, projects the input features onto points of the trained model and determines an orientation of the input object that most likely generates the features extracted from input object.
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Citations
41 Claims
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1. A method for estimating the orientation of an object comprising:
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providing a trained model of the object as training data, wherein the trained model of the object is produced by extracting unique features of the training data, projecting the features of the training data onto corresponding points of a model and determining a probability density function estimation for each model point;
extracting unique features of an image representing the object;
back projecting the features of the image onto points of the trained model; and
determining an estimated orientation of the object that most likely generates the features extracted from object. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. An orientation system for estimating the orientation of an object comprising a pose estimation module that receives a trained model of the object and an input object and extracts unique features of the input object, back projects the features onto points of the trained model and determines an orientation of the input object that most likely generates the features extracted from input object;
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wherein the estimation module uses a predictive prior to bias the output estimation of orientation. - View Dependent Claims (21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32)
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33. A method for determining the orientation of a head, comprising:
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extracting unique features of training data representing different heads;
projecting the features of the training data onto corresponding points of a model;
determining a probability density function estimation for each model point;
extracting unique features of the head;
back projecting the features of the head onto points of the trained model; and
determining an estimated orientation of the head that most likely generates the features extracted from head. - View Dependent Claims (34, 35, 36, 37, 38, 39, 40, 41)
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Specification