OBJECT DETECTION USING DEEP NEURAL NETWORKS
First Claim
1. A computer-implemented method comprising:
- receiving an input image;
generating a full object mask by providing the input image to a first deep neural network object detector that produces a full object mask for an object of a particular object type depicted in the input image, wherein the full object mask identifies regions of the input image that correspond to the object and regions of the input image that do not correspond to the object;
generating a partial object mask by providing the input image to a second deep neural network object detector that produces a partial object mask for a portion of the object of the particular object type depicted in the input image; and
determining a bounding box for the object in the image using the full object mask and the partial object mask.
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Accused Products
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting objects in images. One of the methods includes receiving an input image. A full object mask is generated by providing the input image to a first deep neural network object detector that produces a full object mask for an object of a particular object type depicted in the input image. A partial object mask is generated by providing the input image to a second deep neural network object detector that produces a partial object mask for a portion of the object of the particular object type depicted in the input image. A bounding box is determined for the object in the image using the full object mask and the partial object mask.
107 Citations
21 Claims
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1. A computer-implemented method comprising:
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receiving an input image; generating a full object mask by providing the input image to a first deep neural network object detector that produces a full object mask for an object of a particular object type depicted in the input image, wherein the full object mask identifies regions of the input image that correspond to the object and regions of the input image that do not correspond to the object; generating a partial object mask by providing the input image to a second deep neural network object detector that produces a partial object mask for a portion of the object of the particular object type depicted in the input image; and determining a bounding box for the object in the image using the full object mask and the partial object mask. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system comprising:
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one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising; receiving an input image; generating a full object mask by providing the input image to a first deep neural network object detector that produces a full object mask for an object of a particular object type depicted in the input image, wherein the full object mask identifies regions of the input image that correspond to the object and regions of the input image that do not correspond to the object; generating a partial object mask by providing the input image to a second deep neural network object detector that produces a partial object mask for a portion of the object of the particular object type depicted in the input image; and determining a bounding box for the object in the image using the full object mask and the partial object mask. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:
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receiving an input image; generating a full object mask by providing the input image to a first deep neural network object detector that produces a full object mask for an object of a particular object type depicted in the input image, wherein the full object mask identifies regions of the input image that correspond to the object and regions of the input image that do not correspond to the object; generating a partial object mask by providing the input image to a second deep neural network object detector that produces a partial object mask for a portion of the object of the particular object type depicted in the input image; and determining a bounding box for the object in the image using the full object mask and the partial object mask.
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Specification