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US 11,893,782 B2Granted
Recurrent deep neural network system for detecting overlays in images
AssigneeThe Nielsen Company (US), LLC
InventorsWilson Harron, Irene Zhu
Life of this patent
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Abstract
In one aspect, an example method includes a processor (1) applying a feature map network to an image to create a feature map comprising a grid of vectors characterizing at least one feature in the image and (2) applying a probability map network to the feature map to create a probability map assigning a probability to the at least one feature in the image, where the assigned probability corresponds to a likelihood that the at least one feature is an overlay. The method further includes the processor determining that the probability exceeds a threshold, and responsive to the processor determining that the probability exceeds the threshold, performing a processing action associated with the at least one feature.
Claims20
A system, comprising:
- a processor;
- and
- a non-transitory computer-readable medium having stored thereon program instructions that, upon execution by the processor, cause the processor to perform a set of acts comprising:
- applying a feature map network to an image to create a feature map, wherein the feature map comprises a grid of vectors characterizing at least one feature in the image;
- applying a probability map network to the feature map to create a probability map assigning a probability to the at least one feature in the image, wherein the assigned probability corresponds to a likelihood that the at least one feature is an overlay;
- determining that the assigned probability exceeds a threshold probability value;
- and
- responsive to determining that the assigned probability exceeds the threshold probability value, (i) removing the at least one feature from the image or (ii) inpainting the at least one feature.
5 more elements
A system, comprising:
- a processor;
- and
- a non-transitory computer-readable medium having stored thereon program instructions that, upon execution by the processor, cause the processor to perform a set of acts comprising:
- applying a feature map network to an image to create a feature map, wherein the feature map comprises a grid of vectors characterizing at least one feature in the image;
- applying a probability map network to the feature map to create a probability map assigning a probability to the at least one feature in the image, wherein the assigned probability corresponds to a likelihood that the at least one feature is an overlay;
- determining that the assigned probability exceeds a threshold probability value;
- and
- responsive to determining that the assigned probability exceeds the threshold probability value, (i) determining compliance with an advertising requirement, (ii) performing optical character recognition (OCR) on the at least one feature, (iii) determining a channel associated with the at least one feature, (iv) determining a show associated with the at least one feature, (v) determining a hyperlink associated with the at least one feature, or (vi) accessing a hyperlinked object associated with the at least one feature.
5 more elements
A system, comprising:
- a processor;
- and
- a non-transitory computer-readable medium having stored thereon program instructions that, upon execution by the processor, cause the processor to perform a set of acts comprising:
- training a feature map network by inputting a plurality of training images and a corresponding plurality of groundtruth masks, each of the training images of the plurality having a respective overlay that is distinct relative other overlays in the plurality of training images, wherein each respective groundtruth mask of the corresponding plurality is the same size as its corresponding training image, and has pixel values of zero everywhere except at locations that overlap with the respective overlay on its corresponding training image;
- applying the trained feature map network to an image to create a feature map, wherein the feature map includes data characterizing a feature in the image relative to other features in the image;
- applying a probability map network to the feature map to create a probability map, wherein the probability map network comprises at least two recurrent layers including at least one vertical recurrent layer and at least one horizontal recurrent layer that are multiplied to provide an output indicative of a probability that the feature in the image is an overlay;
- determining that the probability exceeds a threshold probability value;
- and
- responsive to determining that the probability exceeds the threshold probability value, carrying out at least one of a first set of acts or a second set of acts,
- wherein the first set of acts comprises:
- (i) determining compliance with an advertising requirement, (ii) performing optical character recognition (OCR) on the feature, (iii) determining a channel associated with the feature, (iv) determining a show associated with the feature, (v) determining a hyperlink associated with the feature, or (vi) accessing a hyperlinked object associated with the feature,
- and wherein the second set of acts comprises:
- (i) removing the at least one feature from the image or (ii) inpainting the at least one feature.
10 more elements
Dependencies are inferred from the claim text.