Method and apparatus for performing object detection
First Claim
Patent Images
1. An apparatus for generating a model that can be used to perform object detection, the apparatus comprising:
- an input interface configured to receive training images; and
a processor in communication with the input interface for receiving training images from the input interface, the processor being configured to perform a training algorithm, the training algorithm processing multiple training images received from the input interface to produce a Gaussian Mixture Model (GMM) comprising at least a first-layer GMM, the first-layer GMM describing spatial attributes of local features contained in an image, the first-layer GMM receiving local feature detection results from a local feature detection algorithm.
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Abstract
An object detection algorithm that generates a two-layer Gaussian Mixture Model (GMM) during a training session, and subsequent to the training session, uses the two-layer GMM to perform face detection. No labeling of local features is needed. The only input that is provided by a user is the setting of a few global parameters for the image being captured during the training session, such as, for example, the person'"'"'s facial pose.
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Citations
28 Claims
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1. An apparatus for generating a model that can be used to perform object detection, the apparatus comprising:
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an input interface configured to receive training images; and a processor in communication with the input interface for receiving training images from the input interface, the processor being configured to perform a training algorithm, the training algorithm processing multiple training images received from the input interface to produce a Gaussian Mixture Model (GMM) comprising at least a first-layer GMM, the first-layer GMM describing spatial attributes of local features contained in an image, the first-layer GMM receiving local feature detection results from a local feature detection algorithm. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. An apparatus for performing object detection, the apparatus comprising:
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an input interface configured to receive images; and a processor in communication with the input interface, the processor being configured to perform a face detection algorithm, the algorithm processing an input image received from the input interface to determine a probability that the input image fits a Gaussian Mixture Model (GMM) comprising at least a first-layer GMM that describes spatial attributes of local features contained in an image, and a local feature detection algorithm, the first-layer GMM receiving local feature detection results from the local feature detection algorithm. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A method for training a model to perform object detection comprising:
processing multiple images in a processor in accordance with a training algorithm to produce a multi-layer Gaussian Mixture Model (GMM) comprising at least first layer GMM and a second-layer GMM, the first-layer GMM describing spatial attributes of local features contained in an image, the second-layer GMM describing intensity variation attributes of local features contained in the image. - View Dependent Claims (16, 17, 18, 19, 20)
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21. A method for performing object detection comprising:
processing an input image in a processor to determine a probability that the input image fits a multi-layer Gaussian Mixture Model (GMM) comprising at least first layer GMM and a second-layer GMM, the first-layer GMM describing spatial attributes of local features contained in an image, the second-layer GMM describing intensity variation attributes of local features contained in the image. - View Dependent Claims (22, 23, 24, 25, 26)
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27. A computer program for generating a model that can be used to perform object detection, the computer program being embodied on a computer-readable medium, the program comprising:
code for performing a training algorithm, the training algorithm processing multiple training images to produce a multi-layer Gaussian Mixture Model (GMM) comprising at least first layer GMM and a second-layer GMM, the first-layer GMM describing spatial attributes of local features contained in an image, the second-layer GMM describing intensity variation attributes of local features contained in the image.
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28. A computer program for performing object detection, the program being embodied on a computer-readable medium, the program comprising:
code for processing an input image to determine a probability that the input image fits a multi-layer Gaussian Mixture Model (GMM) comprising at least first layer GMM and a second-layer GMM, the first-layer GMM describing spatial attributes of local features contained in an image, the second-layer GMM describing intensity variation attributes of local features contained in the image.
Specification