Spoofed face detection
First Claim
1. A computing device, comprising:
- a processor configured to;
compute a first feature distance between registered image data of a human face in a first spectral region and test image data of the human face in the first spectral region;
compute a second feature distance between the registered image data of the human face in the first spectral region and test image data of the human face in a second spectral region;
compute a test feature distance between the test image data of the human face in the first spectral region and the test image data of the human face in the second spectral region;
determine, based on a predetermined relationship differentiating between real human face image data and spoofed human face image data, whether the human face to which the test image data in the first and second spectral regions corresponds is a real human face or a spoofed human face; and
modify a behavior of the computing device based on whether the human face is determined to be the real human face or the spoofed human face.
1 Assignment
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Accused Products
Abstract
Examples are disclosed herein that relate to detecting spoofed human faces. One example provides a computing device comprising a processor configured to compute a first feature distance between registered image data of a human face in a first spectral region and test image data of the human face in the first spectral region, compute a second feature distance between the registered image data and test image data of the human face in a second spectral region, compute a test feature distance between the test image data in the first spectral region and the test image data in the second spectral region, determine, based on a predetermined relationship, whether the human face to which the test image data in the first and second spectral regions corresponds is a real human face or a spoofed human face, and modify a behavior of the computing device.
26 Citations
20 Claims
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1. A computing device, comprising:
a processor configured to; compute a first feature distance between registered image data of a human face in a first spectral region and test image data of the human face in the first spectral region; compute a second feature distance between the registered image data of the human face in the first spectral region and test image data of the human face in a second spectral region; compute a test feature distance between the test image data of the human face in the first spectral region and the test image data of the human face in the second spectral region; determine, based on a predetermined relationship differentiating between real human face image data and spoofed human face image data, whether the human face to which the test image data in the first and second spectral regions corresponds is a real human face or a spoofed human face; and modify a behavior of the computing device based on whether the human face is determined to be the real human face or the spoofed human face. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method of biometric verification, comprising:
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computing a first feature distance between registered image data of a human face in a first spectral region and test image data of the human face in the first spectral region; computing a second feature distance between the registered image data of the human face in the first spectral region and test image data of the human face in a second spectral region; computing a test feature distance between the test image data of the human face in the first spectral region and the test image data of the human face in the second spectral region; determining, based on a predetermined relationship differentiating between real human image data and spoofed human image data, whether the human face to which the test image data in the first and second spectral regions corresponds is a real human face or a spoofed human face; and modifying a behavior of a computing device based on whether the human face is determined to be the real human face or the spoofed human face. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19)
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20. A computing device, comprising:
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a processor; and memory holding instructions executable by the processor to; receive registered image data of a human face in a first spectral region; receive test image data of the human face in the first spectral region; receive test image data of the human face in a second spectral region; for each of the registered image data, the test image data in the first spectral region, and the test image data in the second spectral region; identify a plurality of regions of interest; extract at least one feature from each of the plurality of regions of interest; and assemble the extracted features into a feature vector; compute a first feature distance between the feature vector of the registered image data and the feature vector of the test image data in the first spectral region; compute a second feature distance between the feature vector of the registered image data and the feature vector of the test image data in the second spectral region; compute a test feature distance between the feature vector of the test image data in the first spectral region and the feature vector of the test image data in the second spectral region; in a two-dimensional feature distance space, separate the first, second, and test feature distances into one of a real human face image data class and a spoofed human face image data class; and derive a classifier from the separated feature distances, the classifier configured to differentiate between real human face image data and spoofed human face image data.
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Specification