Patents by Inventor Joseph LEMLEY
Joseph LEMLEY 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: 20230394120Abstract: Disclosed is a multi-modal convolutional neural network (CNN) for fusing image information from a frame based camera, such as, a near infra-red (NIR) camera and an event camera for analysing facial characteristics in order to produce classifications such as head pose or eye gaze. The neural network processes image frames acquired from each camera through a plurality of convolutional layers to provide a respective set of one or more intermediate images. The network fuses at least one corresponding pair of intermediate images generated from each of image frames through an array of fusing cells. Each fusing cell is connected to at least a respective element of each intermediate image and is trained to weight each element from each intermediate image to provide the fused output. The neural network further comprises at least one task network configured to generate one or more task outputs for the region of interest.Type: ApplicationFiled: August 17, 2023Publication date: December 7, 2023Inventors: Cian Ryan, Richard Blythman, Joseph Lemley, Paul Kielty
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Patent number: 11768919Abstract: Disclosed is a multi-modal convolutional neural network (CNN) for fusing image information from a frame based camera, such as, a near infra-red (NIR) camera and an event camera for analysing facial characteristics in order to produce classifications such as head pose or eye gaze. The neural network processes image frames acquired from each camera through a plurality of convolutional layers to provide a respective set of one or more intermediate images. The network fuses at least one corresponding pair of intermediate images generated from each of image frames through an array of fusing cells. Each fusing cell is connected to at least a respective element of each intermediate image and is trained to weight each element from each intermediate image to provide the fused output. The neural network further comprises at least one task network configured to generate one or more task outputs for the region of interest.Type: GrantFiled: January 13, 2021Date of Patent: September 26, 2023Inventors: Cian Ryan, Richard Blythman, Joseph Lemley, Paul Kielty
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Patent number: 11699293Abstract: A neural network image processing apparatus arranged to acquire images from an image sensor and to: identify a ROI containing a face region in an image; determine at plurality of facial landmarks in the face region; use the facial landmarks to transform the face region within the ROI into a face region having a given pose; and use transformed landmarks within the transformed face region to identify a pair of eye regions within the transformed face region. Each identified eye region is fed to a respective first and second convolutional neural network, each network configured to produce a respective feature vector. Each feature vector is fed to respective eyelid opening level neural networks to obtain respective measures of eyelid opening for each eye region. The feature vectors are combined and to a gaze angle neural network to generate gaze yaw and pitch values substantially simultaneously with the eyelid opening values.Type: GrantFiled: February 22, 2022Date of Patent: July 11, 2023Inventors: Joseph Lemley, Liviu-Cristian Dutu, Stefan Mathe, Madalin Dumitru-Guzu, Dan Filip
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Publication number: 20230107097Abstract: A method for identifying a gesture from one of a plurality of dynamic gestures, each dynamic gesture comprising a distinct movement made by a user over a period of time within a field of view of an image acquisition device comprises iteratively: acquiring a current image from said image acquisition device at a given time; and passing at least a portion of the current image through a bidirectionally recurrent multi-layer classifier. A final layer of the multi-layer classifier comprises an output indicating a probability that a gesture from the plurality of dynamic gestures is being made by a user during the time of acquiring the image.Type: ApplicationFiled: October 6, 2021Publication date: April 6, 2023Applicant: FotoNation LimitedInventors: Tudor TOPOLEANU, Szabolcs FULOP, Petronel BIGIOI, Cian RYAN, Joseph LEMLEY
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Publication number: 20220277172Abstract: A method for training a neural network for detecting a plurality of classes of object within a sample comprises providing a training data set comprising a plurality of samples, each annotated according to whether the samples include labelled objects of interest. In a first type of samples, all objects of interest are labelled according to their class and comprise a foreground of said samples, the remainder of the samples comprising background. In a second type of samples, some objects of interest are labelled in a foreground and their background may comprise unlabelled objects. A third type of samples comprise only background comprising no objects of interest. Negative mining is only performed on the results of processing the first and third types of samples.Type: ApplicationFiled: March 1, 2021Publication date: September 1, 2022Applicant: FotoNation LimitedInventors: Eoin O'CONNELL, Joseph LEMLEY
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Publication number: 20220222496Abstract: Disclosed is a multi-modal convolutional neural network (CNN) for fusing image information from a frame based camera, such as, a near infra-red (NIR) camera and an event camera for analysing facial characteristics in order to produce classifications such as head pose or eye gaze. The neural network processes image frames acquired from each camera through a plurality of convolutional layers to provide a respective set of one or more intermediate images. The network fuses at least one corresponding pair of intermediate images generated from each of image frames through an array of fusing cells. Each fusing cell is connected to at least a respective element of each intermediate image and is trained to weight each element from each intermediate image to provide the fused output. The neural network further comprises at least one task network configured to generate one or more task outputs for the region of interest.Type: ApplicationFiled: January 13, 2021Publication date: July 14, 2022Applicant: FotoNation LimitedInventors: Cian RYAN, Richard BLYTHMAN, Joseph LEMLEY, Paul KIELTY
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Publication number: 20220171458Abstract: A neural network image processing apparatus arranged to acquire images from an image sensor and to: identify a ROI containing a face region in an image; determine at plurality of facial landmarks in the face region; use the facial landmarks to transform the face region within the ROI into a face region having a given pose; and use transformed landmarks within the transformed face region to identify a pair of eye regions within the transformed face region. Each identified eye region is fed to a respective first and second convolutional neural network, each network configured to produce a respective feature vector. Each feature vector is fed to respective eyelid opening level neural networks to obtain respective measures of eyelid opening for each eye region. The feature vectors are combined and to a gaze angle neural network to generate gaze yaw and pitch values substantially simultaneously with the eyelid opening values.Type: ApplicationFiled: February 22, 2022Publication date: June 2, 2022Inventors: Joseph Lemley, Liviu-Cristian Dutu, Stefan Mathe, Madalin Dumitru-Guzu, Dan Filip
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Patent number: 11314324Abstract: A neural network image processing apparatus arranged to acquire images from an image sensor and to: identify a ROI containing a face region in an image; determine at plurality of facial landmarks in the face region; use the facial landmarks to transform the face region within the ROI into a face region having a given pose; and use transformed landmarks within the transformed face region to identify a pair of eye regions within the transformed face region. Each identified eye region is fed to a respective first and second convolutional neural network, each network configured to produce a respective feature vector. Each feature vector is fed to respective eyelid opening level neural networks to obtain respective measures of eyelid opening for each eye region. The feature vectors are combined and to a gaze angle neural network to generate gaze yaw and pitch values substantially simultaneously with the eyelid opening values.Type: GrantFiled: February 3, 2020Date of Patent: April 26, 2022Assignee: FotoNation LimitedInventors: Joseph Lemley, Liviu-Cristian Dutu, Stefan Mathe, Madalin Dumitru-Guzu, Dan Filip
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Publication number: 20200342212Abstract: A neural network image processing apparatus arranged to acquire images from an image sensor and to: identify a ROI containing a face region in an image; determine at plurality of facial landmarks in the face region; use the facial landmarks to transform the face region within the ROI into a face region having a given pose; and use transformed landmarks within the transformed face region to identify a pair of eye regions within the transformed face region. Each identified eye region is fed to a respective first and second convolutional neural network, each network configured to produce a respective feature vector. Each feature vector is fed to respective eyelid opening level neural networks to obtain respective measures of eyelid opening for each eye region. The feature vectors are combined and to a gaze angle neural network to generate gaze yaw and pitch values substantially simultaneously with the eyelid opening values.Type: ApplicationFiled: February 3, 2020Publication date: October 29, 2020Applicant: FotoNation LimitedInventors: Joseph LEMLEY, Liviu-Cristian DUTU, Stefan MATHE, Madalin DUMITRU-GUZU, Dan FILIP
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Patent number: 10684681Abstract: A neural network image processing apparatus arranged to acquire images from an image sensor and to: identify a ROI containing a face region in an image; determine at plurality of facial landmarks in the face region; use the facial landmarks to transform the face region within the ROI into a face region having a given pose; and use transformed landmarks within the transformed face region to identify a pair of eye regions within the transformed face region. Each identified eye region is fed to a respective first and second convolutional neural network, each network configured to produce a respective feature vector. Each feature vector is fed to respective eyelid opening level neural networks to obtain respective measures of eyelid opening for each eye region. The feature vectors are combined and to a gaze angle neural network to generate gaze yaw and pitch values substantially simultaneously with the eyelid opening values.Type: GrantFiled: June 11, 2018Date of Patent: June 16, 2020Assignee: FotoNation LimitedInventors: Joseph Lemley, Liviu-Cristian Dutu, Stefan Mathe, Madalin Dumitru-Guzu
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Publication number: 20190377409Abstract: A neural network image processing apparatus arranged to acquire images from an image sensor and to: identify a ROI containing a face region in an image; determine at plurality of facial landmarks in the face region; use the facial landmarks to transform the face region within the ROI into a face region having a given pose; and use transformed landmarks within the transformed face region to identify a pair of eye regions within the transformed face region. Each identified eye region is fed to a respective first and second convolutional neural network, each network configured to produce a respective feature vector. Each feature vector is fed to respective eyelid opening level neural networks to obtain respective measures of eyelid opening for each eye region. The feature vectors are combined and to a gaze angle neural network to generate gaze yaw and pitch values substantially simultaneously with the eyelid opening values.Type: ApplicationFiled: June 11, 2018Publication date: December 12, 2019Applicant: FotoNation LimitedInventors: Joseph LEMLEY, Liviu-Cristian DUTU, Stefan MATHE, Madalin DUMITRU-GUZU