Patents by Inventor Paul Brasnett
Paul Brasnett has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240135139Abstract: Methods and systems for implementing a traditional computer vision algorithm as a neural network. The method includes: receiving a definition of the traditional computer vision algorithm that identifies a sequence of one or more traditional computer vision algorithm operations; mapping each of the one or more traditional computer vision algorithm operations to a set of one or more neural network primitives that is mathematically equivalent to that traditional computer vision algorithm operation; linking the one or more network primitives mapped to each traditional computer vision algorithm operation according to the sequence to form a neural network representing the traditional computer vision algorithm; and configuring hardware logic capable of implementing a neural network to implement the neural network that represents the traditional computer vision algorithm.Type: ApplicationFiled: April 19, 2023Publication date: April 25, 2024Inventors: Paul Brasnett, Daniel Valdez Balderas, Cagatay Dikici, Szabolcs Csefalvay, David Hough, Timothy Smith, James Imber
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Publication number: 20230419453Abstract: A reduced noise image can be formed from a set of images. One of the images of the set can be selected to be a reference image and other images of the set are transformed such that they are better aligned with the reference image. A measure of the alignment of each image with the reference image is determined. At least some of the transformed images can then be combined using weights which depend on the alignment of the transformed image with the reference image to thereby form the reduced noise image. By weighting the images according to their alignment with the reference image the effects of misalignment between the images in the combined image are reduced. Furthermore, motion correction may be applied to the reduced noise image.Type: ApplicationFiled: September 11, 2023Publication date: December 28, 2023Inventors: Marc Vivet, Paul Brasnett
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Patent number: 11756162Abstract: A reduced noise image can be formed from a set of images. One of the images of the set can be selected to be a reference image and other images of the set are transformed such that they are better aligned with the reference image. A measure of the alignment of each image with the reference image is determined. At least some of the transformed images can then be combined using weights which depend on the alignment of the transformed image with the reference image to thereby form the reduced noise image. By weighting the images according to their alignment with the reference image the effects of misalignment between the images in the combined image are reduced. Furthermore, motion correction may be applied to the reduced noise image.Type: GrantFiled: March 14, 2016Date of Patent: September 12, 2023Assignee: Imagination Technologies LimitedInventors: Marc Vivet, Paul Brasnett
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Publication number: 20230196503Abstract: In an example method and system, image data to an image processing module. Image data is read from memory into a down-scaler, which down-scales the image data to a first resolution, which is stored in a first buffer. A region of image data which the image processing module will request is predicted, and image data corresponding to at least part of the predicted region of image data is stored in a first buffer, in a second resolution, higher than the first. When a request for image data is received, it is then determined whether image data corresponding to the requested image data is in the second buffer, and if so, then image data is provided to the image processing module from the second buffer. If not, then image data from the first buffer is up-scaled, and the up-scaled image data is provided to the image processing module.Type: ApplicationFiled: February 16, 2023Publication date: June 22, 2023Inventors: Paul Brasnett, Jonathan Diggins, Steven Fishwick, Stephen Morphet
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Patent number: 11636306Abstract: Methods and systems for implementing a traditional computer vision algorithm as a neural network. The method includes: receiving a definition of the traditional computer vision algorithm that identifies a sequence of one or more traditional computer vision algorithm operations; mapping each of the one or more traditional computer vision algorithm operations to a set of one or more neural network primitives that is mathematically equivalent to that traditional computer vision algorithm operation; linking the one or more network primitives mapped to each traditional computer vision algorithm operation according to the sequence to form a neural network representing the traditional computer vision algorithm; and configuring hardware logic capable of implementing a neural network to implement the neural network that represents the traditional computer vision algorithm.Type: GrantFiled: May 21, 2019Date of Patent: April 25, 2023Assignee: Imagination Technologies LimitedInventors: Paul Brasnett, Daniel Valdez Balderas, Cagatay Dikici, Szabolcs Cséfalvay, David Hough, Timothy Smith, James Imber
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Patent number: 11587199Abstract: In an example method and system, image data to an image processing module. Image data is read from memory into a down-scaler, which down-scales the image data to a first resolution, which is stored in a first buffer. A region of image data which the image processing module will request is predicted, and image data corresponding to at least part of the predicted region of image data is stored in a first buffer, in a second resolution, higher than the first. When a request for image data is received, it is then determined whether image data corresponding to the requested image data is in the second buffer, and if so, then image data is provided to the image processing module from the second buffer. If not, then image data from the first buffer is up-scaled, and the up-scaled image data is provided to the image processing module.Type: GrantFiled: September 21, 2018Date of Patent: February 21, 2023Assignee: Imagination Technologies LimitedInventors: Paul Brasnett, Jonathan Diggins, Steven Fishwick, Stephen Morphet
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Patent number: 11282216Abstract: A reduced noise image can be formed from a set of images. One of the images of the set can be selected to be a reference image and other images of the set are transformed such that they are better aligned with the reference image. A measure of the alignment of each image with the reference image is determined. At least some of the transformed images can then be combined using weights which depend on the alignment of the transformed image with the reference image to thereby form the reduced noise image. By weighting the images according to their alignment with the reference image the effects of misalignment between the images in the combined image are reduced. Furthermore, motion correction may be applied to the reduced noise image.Type: GrantFiled: May 4, 2020Date of Patent: March 22, 2022Assignee: Imagination Technologies LimitedInventors: Marc Vivet, Paul Brasnett
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Publication number: 20220067497Abstract: Methods and system for converting a plurality of weights of a filter of a Deep Neural Network (DNN) in a first number format to a second number format, the second number format having less precision than the first number format, to enable the DNN to be implemented in hardware logic.Type: ApplicationFiled: November 11, 2021Publication date: March 3, 2022Inventors: Cagatay Dikici, Paul Brasnett, Muhammad Asad, Stephen Morphet
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Patent number: 11188817Abstract: Methods and system for converting a plurality of weights of a filter of a Deep Neural Network (DNN) in a first number format to a second number format, the second number format having less precision than the first number format, to enable the DNN to be implemented in hardware logic.Type: GrantFiled: August 24, 2020Date of Patent: November 30, 2021Assignee: Imagination Technologies LimitedInventors: Cagatay Dikici, Paul Brasnett, Muhammad Asad, Stephen Morphet
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Patent number: 11184509Abstract: An interlaced video signal can include content of different types, such as interlaced content and progressive content. The progressive content may have different cadences according to the ratio between the frame rate of the progressive content and the field rate of the interlaced video signal. Cadence analysis is performed to identify the cadence of the video signal and/or to determine field pairings when progressive content is included. As described herein, motion information (e.g. motion vectors) for blocks of fields of a video signal can be used for the cadence analysis. The use of motion information provides a robust method of performing cadence analysis.Type: GrantFiled: April 9, 2018Date of Patent: November 23, 2021Assignee: Imagination Technologies LimitedInventor: Paul Brasnett
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Publication number: 20210073614Abstract: Methods and system for converting a plurality of weights of a filter of a Deep Neural Network (DNN) in a first number format to a second number format, the second number format having less precision than the first number format, to enable the DNN to be implemented in hardware logic.Type: ApplicationFiled: August 24, 2020Publication date: March 11, 2021Inventors: Cagatay Dikici, Paul Brasnett, Muhammad Asad, Stephen Morphet
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Publication number: 20200265595Abstract: A reduced noise image can be formed from a set of images. One of the images of the set can be selected to be a reference image and other images of the set are transformed such that they are better aligned with the reference image. A measure of the alignment of each image with the reference image is determined. At least some of the transformed images can then be combined using weights which depend on the alignment of the transformed image with the reference image to thereby form the reduced noise image. By weighting the images according to their alignment with the reference image the effects of misalignment between the images in the combined image are reduced. Furthermore, motion correction may be applied to the reduced noise image.Type: ApplicationFiled: May 4, 2020Publication date: August 20, 2020Inventors: Marc Vivet, Paul Brasnett
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Patent number: 10679363Abstract: A reduced noise image can be formed from a set of images. One of the images of the set can be selected to be a reference image and other images of the set are transformed such that they are better aligned with the reference image. A measure of the alignment of each image with the reference image is determined. At least some of the transformed images can then be combined using weights which depend on the alignment of the transformed image with the reference image to thereby form the reduced noise image. By weighting the images according to their alignment with the reference image the effects of misalignment between the images in the combined image are reduced. Furthermore, motion correction may be applied to the reduced noise image.Type: GrantFiled: January 23, 2018Date of Patent: June 9, 2020Assignee: Imagination Technologies LimitedInventors: Marc Vivet, Paul Brasnett
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Publication number: 20190354844Abstract: Methods and systems for implementing a traditional computer vision algorithm as a neural network. The method includes: receiving a definition of the traditional computer vision algorithm that identifies a sequence of one or more traditional computer vision algorithm operations; mapping each of the one or more traditional computer vision algorithm operations to a set of one or more neural network primitives that is mathematically equivalent to that traditional computer vision algorithm operation; linking the one or more network primitives mapped to each traditional computer vision algorithm operation according to the sequence to form a neural network representing the traditional computer vision algorithm; and configuring hardware logic capable of implementing a neural network to implement the neural network that represents the traditional computer vision algorithm.Type: ApplicationFiled: May 21, 2019Publication date: November 21, 2019Inventors: Paul Brasnett, Daniel Valdez Balderas, Cagatay Dikici, Szabolcs Cséfalvay, David Hough, Timothy Smith, James Imber
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Publication number: 20190087718Abstract: Hardware implementations of DNNs and related methods with a variable output data format. Specifically, in the hardware implementations and methods described herein the hardware implementation is configured to perform one or more hardware passes to implement a DNN wherein during each hardware pass the hardware implementation receives input data for a particular layer, processes that input data in accordance with the particular layer (and optionally one or more subsequent layers), and outputs the processed data in a desired format based on the layer, or layers, that are processed in the particular hardware pass. In particular, when a hardware implementation receives input data to be processed, the hardware implementation also receives information indicating the desired format for the output data of the hardware pass and the hardware implementation is configured to, prior to outputting the processed data convert the output data to the desired format.Type: ApplicationFiled: September 20, 2018Publication date: March 21, 2019Inventors: Chris Martin, David Hough, Paul Brasnett, Cagatay Dikici, James Imber, Clifford Gibson
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Publication number: 20190026857Abstract: In an example method and system, image data to an image processing module. Image data is read from memory into a down-scaler, which down-scales the image data to a first resolution, which is stored in a first buffer. A region of image data which the image processing module will request is predicted, and image data corresponding to at least part of the predicted region of image data is stored in a first buffer, in a second resolution, higher than the first. When a request for image data is received, it is then determined whether image data corresponding to the requested image data is in the second buffer, and if so, then image data is provided to the image processing module from the second buffer. If not, then image data from the first buffer is up-scaled, and the up-scaled image data is provided to the image processing module.Type: ApplicationFiled: September 21, 2018Publication date: January 24, 2019Inventors: Paul Brasnett, Jonathan Diggins, Steven Fishwick, Stephen Morphet
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Patent number: 10109032Abstract: In an example method and system, image data to an image processing module. Image data is read from memory into a down-scaler, which down-scales the image data to a first resolution, which is stored in a first buffer. A region of image data which the image processing module will request is predicted, and image data corresponding to at least part of the predicted region of image data is stored in a first buffer, in a second resolution, higher than the first. When a request for image data is received, it is then determined whether image data corresponding to the requested image data is in the second buffer, and if so, then image data is provided to the image processing module from the second buffer. If not, then image data from the first buffer is up-scaled, and the up-scaled image data is provided to the image processing module.Type: GrantFiled: March 13, 2013Date of Patent: October 23, 2018Assignee: Imagination Technologies LimtedInventors: Paul Brasnett, Jonathan Diggins, Steven Fishwick, Stephen Morphet
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Patent number: 10055639Abstract: A data processing system for performing face detection on a stream of frames of image data, the data processing system comprising: a skin patch identifier configured to identify one or more patches of skin color in a first frame and characterize each patch in the first frame using a respective patch construct of a predefined shape; a first search tile generator configured to generate one or more first search tiles from the one or more patch constructs; and a face detector configured to detect faces in the stream by performing face detection in one or more frames of the stream within the first search tiles.Type: GrantFiled: March 21, 2017Date of Patent: August 21, 2018Assignee: Imagination Technologies LimitedInventors: Szabolcs Cséfalvay, Paul Brasnett
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Publication number: 20180227465Abstract: An interlaced video signal can include content of different types, such as interlaced content and progressive content. The progressive content may have different cadences according to the ratio between the frame rate of the progressive content and the field rate of the interlaced video signal. Cadence analysis is performed to identify the cadence of the video signal and/or to determine field pairings when progressive content is included. As described herein, motion information (e.g. motion vectors) for blocks of fields of a video signal can be used for the cadence analysis. The use of motion information provides a robust method of performing cadence analysis.Type: ApplicationFiled: April 9, 2018Publication date: August 9, 2018Inventor: Paul Brasnett
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Publication number: 20180150959Abstract: A reduced noise image can be formed from a set of images. One of the images of the set can be selected to be a reference image and other images of the set are transformed such that they are better aligned with the reference image. A measure of the alignment of each image with the reference image is determined. At least some of the transformed images can then be combined using weights which depend on the alignment of the transformed image with the reference image to thereby form the reduced noise image. By weighting the images according to their alignment with the reference image the effects of misalignment between the images in the combined image are reduced. Furthermore, motion correction may be applied to the reduced noise image.Type: ApplicationFiled: January 23, 2018Publication date: May 31, 2018Inventors: Marc Vivet, Paul Brasnett