Devices and methods for identifying an object in an image
First Claim
1. A computer-implemented method for identifying an object in an image, the method comprising:
- receiving, by one or more processors, an image having one or more objects of interest;
using a first neural network to identify an approximate position of an object of interest in the received image;
identifying, by the one or more processors, based on the identified approximate position, a section of the received image that includes the object of interest;
obtaining, by the one or more processors, a plurality of sub-images corresponding to the identified section of the received image;
applying the plurality of sub-images to a plurality of second neural networks, each of the second neural networks determining a respective position of the object of interest, such that the plurality of second neural networks determine a respective plurality of second positions of the object of interest; and
statistically analyzing the plurality of second positions to determine an output position of the object of interest.
1 Assignment
0 Petitions
Accused Products
Abstract
Methods, devices, and computer-readable storage media for identifying an object in an image, the method including using a first neural network to identify an approximate position of an object of interest in an image and identifying based on the approximate position, a section of the image that includes the object of interest. A plurality of sub-images corresponding to the identified section of the image are applied to a plurality of second neural networks to determine a plurality of second positions of the object of interest. The plurality of second positions are statistically analyzed to determine an output position of the object of interest.
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Citations
27 Claims
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1. A computer-implemented method for identifying an object in an image, the method comprising:
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receiving, by one or more processors, an image having one or more objects of interest; using a first neural network to identify an approximate position of an object of interest in the received image; identifying, by the one or more processors, based on the identified approximate position, a section of the received image that includes the object of interest; obtaining, by the one or more processors, a plurality of sub-images corresponding to the identified section of the received image; applying the plurality of sub-images to a plurality of second neural networks, each of the second neural networks determining a respective position of the object of interest, such that the plurality of second neural networks determine a respective plurality of second positions of the object of interest; and statistically analyzing the plurality of second positions to determine an output position of the object of interest. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A device for identifying objects in an image, the device comprising:
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an input interface that receives an image having one or more objects of interest; at least one storage device configured to store the received image; and one or more processors configured to; use a first neural network to identify an approximate position of an object of interest; identify, based on the identified approximate position, a section of the received image that includes the object of interest; obtain a plurality of sub-images corresponding to the identified section of the received image; apply the plurality of sub-images to a plurality of second neural networks, each of the second neural networks determining a respective position of the object of interest, such that the plurality of second neural networks determine a respective plurality of second positions of first object of interest; and statistically analyze the plurality of second positions to determine an output position of the object of interest. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A non-transitory computer-readable medium storing instructions that, when executable by one or more processors, cause the one or more processors to perform a method for identifying an object in an image, the method comprising:
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receiving an image having one or more objects of interest; using a first neural network to identify an approximate position of an object of interest the received image; identifying based on the identified approximate position, a section of the received image that includes the object of interest; obtaining a plurality of sub-images corresponding to the identified section of the received image; applying the plurality of sub-images to a plurality of second neural networks, each of the second neural networks determining a respective position of the object of interest, such that the plurality of second neural networks determine a respective plurality of second positions of the object of interest; and statistically analyzing the plurality of second positions to determine an output position of the object of interest. - View Dependent Claims (20, 21, 22, 23, 24, 25, 26, 27)
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Specification