Patents by Inventor David Macdara Moloney
David Macdara Moloney 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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Patent number: 11965743Abstract: A volumetric data structure models a particular volume representing the particular volume at a plurality of levels of detail. A first entry in the volumetric data structure includes a first set of bits representing voxels at a first level of detail, the first level of detail includes the lowest level of detail in the volumetric data structure, values of the first set of bits indicate whether a corresponding one of the voxels is at least partially occupied by respective geometry, where the volumetric data structure further includes a number of second entries representing voxels at a second level of detail higher than the first level of detail, the voxels at the second level of detail represent subvolumes of volumes represented by voxels at the first level of detail, and the number of second entries corresponds to a number of bits in the first set of bits with values indicating that a corresponding voxel volume is occupied.Type: GrantFiled: June 18, 2022Date of Patent: April 23, 2024Assignee: Movidius LimitedInventors: David Macdara Moloney, Jonathan David Byrne
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Publication number: 20240127068Abstract: A machine learning system is provided to enhance various aspects of machine learning models. In some aspects. a substantially photorealistic three-dimensional (3D) graphical model of an object is accessed and a set of training images of the 3D graphical mode are generated, the set of training images generated to add imperfections and degrade photorealistic quality of the training images. The set of training images are provided as training data to train an artificial neural network.Type: ApplicationFiled: December 12, 2023Publication date: April 18, 2024Applicant: MOVIDIUS LTD.Inventors: David Macdara Moloney, Jonathan David Byrne, Léonie Raideen Buckley, Xiaofan Xu, Dexmont Alejandro Peña Carillo, Luis M. Rodríguez Martín de la Sierra, Carlos Márquez Rodríguez-Peral, Mi Sun Park, Cormac M. Brick, Alessandro Palla
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Publication number: 20240118086Abstract: A volumetric data structure models a particular volume representing the particular volume at a plurality of levels of detail. A first entry in the volumetric data structure includes a first set of bits representing voxels at a first level of detail, the first level of detail includes the lowest level of detail in the volumetric data structure, values of the first set of bits indicate whether a corresponding one of the voxels is at least partially occupied by respective geometry, where the volumetric data structure further includes a number of second entries representing voxels at a second level of detail higher than the first level of detail, the voxels at the second level of detail represent subvolumes of volumes represented by voxels at the first level of detail, and the number of second entries corresponds to a number of bits in the first set of bits with values indicating that a corresponding voxel volume is occupied.Type: ApplicationFiled: October 30, 2023Publication date: April 11, 2024Inventors: David Macdara Moloney, Jonathan David Byrne
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Publication number: 20240094003Abstract: A ray is cast into a volume described by a volumetric data structure, which describes the volume at a plurality of levels of detail. A first entry in the volumetric data structure includes a first set of bits representing voxels at a lowest one of the plurality of levels of detail, and values of the first set of bits indicate whether a corresponding one of the voxels is at least partially occupied by respective geometry. A set of second entries in the volumetric data structure describe voxels at a second level of detail, which represent subvolumes of the voxels at the first lowest level of detail. The ray is determined to pass through a particular subset of the voxels at the first level of detail and at least a particular one of the particular subset of voxels is determined to be occupied by geometry.Type: ApplicationFiled: June 16, 2023Publication date: March 21, 2024Applicant: Movidius Ltd.Inventors: Sam Caulfield, David Macdara Moloney, Gary Garfield Barrington Baugh
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Patent number: 11920934Abstract: A view of geometry captured in image data generated by an imaging sensor is compared with a description of the geometry in a volumetric data structure. The volumetric data structure describes the volume at a plurality of levels of detail and includes entries describing voxels defining subvolumes of the volume at multiple levels of detail. The volumetric data structure includes a first entry to describe voxels at a lowest one of the levels of detail and further includes a number of second entries to describe voxels at a higher, second level of detail, the voxels at the second level of detail representing subvolumes of the voxels at the first level of detail. Each of these entries include bits to indicate whether a corresponding one of the voxels is at least partially occupied with the geometry. One or more of these entries are used in the comparison with the image data.Type: GrantFiled: June 14, 2021Date of Patent: March 5, 2024Assignee: Movidius LimitedInventors: David Macdara Moloney, Jonathan David Byrne
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Patent number: 11900256Abstract: A machine learning system is provided to enhance various aspects of machine learning models. In some aspects, a substantially photorealistic three-dimensional (3D) graphical model of an object is accessed and a set of training images of the 3D graphical mode are generated, the set of training images generated to add imperfections and degrade photorealistic quality of the training images. The set of training images are provided as training data to train an artificial neural network.Type: GrantFiled: May 21, 2019Date of Patent: February 13, 2024Assignee: Intel CorporationInventors: David Macdara Moloney, Jonathan David Byrne, Léonie Raideen Buckley, Xiaofan Xu, Dexmont Alejandro Peña Carillo, Luis M. Rodríguez Martín de la Sierra, Carlos Márquez Rodríguez-Peral, Mi Sun Park, Cormac M. Brick, Alessandro Palla
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Publication number: 20240011777Abstract: An output of a first one of a plurality of layers within a neural network is identified. A bitmap is determined from the output, the bitmap including a binary matrix. A particular subset of operations for a second one of the plurality of layers is determined to be skipped based on the bitmap. Operations are performed for the second layer other than the particular subset of operations, while the particular subset of operations are skipped.Type: ApplicationFiled: January 27, 2023Publication date: January 11, 2024Applicant: Movidius Ltd.Inventors: David Macdara Moloney, Xiaofan Xu
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Patent number: 11680803Abstract: A ray is cast into a volume described by a volumetric data structure, which describes the volume at a plurality of levels of detail. A first entry in the volumetric data structure includes a first set of bits representing voxels at a lowest one of the plurality of levels of detail, and values of the first set of bits indicate whether a corresponding one of the voxels is at least partially occupied by respective geometry. A set of second entries in the volumetric data structure describe voxels at a second level of detail, which represent subvolumes of the voxels at the first lowest level of detail. The ray is determined to pass through a particular subset of the voxels at the first level of detail and at least a particular one of the particular subset of voxels is determined to be occupied by geometry.Type: GrantFiled: January 7, 2022Date of Patent: June 20, 2023Assignee: Movidius Ltd.Inventors: Sam Caulfield, David Macdara Moloney, Gary Garfield Barrington Baugh
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Patent number: 11593987Abstract: An output of a first one of a plurality of layers within a neural network is identified. A bitmap is determined from the output, the bitmap including a binary matrix. A particular subset of operations for a second one of the plurality of layers is determined to be skipped based on the bitmap. Operations are performed for the second layer other than the particular subset of operations, while the particular subset of operations are skipped.Type: GrantFiled: December 7, 2020Date of Patent: February 28, 2023Assignee: Movidius Ltd.Inventors: David Macdara Moloney, Xiaofan Xu
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Publication number: 20230044729Abstract: A volumetric data structure models a particular volume representing the particular volume at a plurality of levels of detail. A first entry in the volumetric data structure includes a first set of bits representing voxels at a first level of detail, the first level of detail includes the lowest level of detail in the volumetric data structure, values of the first set of bits indicate whether a corresponding one of the voxels is at least partially occupied by respective geometry, where the volumetric data structure further includes a number of second entries representing voxels at a second level of detail higher than the first level of detail, the voxels at the second level of detail represent subvolumes of volumes represented by voxels at the first level of detail, and the number of second entries corresponds to a number of bits in the first set of bits with values indicating that a corresponding voxel volume is occupied.Type: ApplicationFiled: June 18, 2022Publication date: February 9, 2023Applicant: Movidius Ltd.Inventors: David Macdara Moloney, Jonathan David Byrne
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Patent number: 11532117Abstract: A particular voxel is identified within a volume and a hash table is used to obtain volumetric data describing the particular voxel within the volume. Values of x-, y- and z-coordinates in the volume associated with the particular voxel are determined an index value associated with the particular voxel is determined according to a hashing algorithm, where the index value is determined from summing weighted values of the x-, y- and z-coordinates, and the weighted values are based on a variable value corresponding to a dimension of the volume. A particular entry is identified in the hash table based on the index value, where the particular entry includes volumetric data, and the volumetric data identifies, for the particular voxel, whether the particular voxel is occupied.Type: GrantFiled: October 16, 2018Date of Patent: December 20, 2022Assignee: Movidius Ltd.Inventors: David Macdara Moloney, Jonathan David Byrne, Leonie Buckley, Gary Garfield Barrington Baugh, Sam Caulfield, Alessandro Palla, Ananya Gupta
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Publication number: 20220237855Abstract: A ray is cast into a volume described by a volumetric data structure, which describes the volume at a plurality of levels of detail. A first entry in the volumetric data structure includes a first set of bits representing voxels at a lowest one of the plurality of levels of detail, and values of the first set of bits indicate whether a corresponding one of the voxels is at least partially occupied by respective geometry. A set of second entries in the volumetric data structure describe voxels at a second level of detail, which represent subvolumes of the voxels at the first lowest level of detail. The ray is determined to pass through a particular subset of the voxels at the first level of detail and at least a particular one of the particular subset of voxels is determined to be occupied by geometry.Type: ApplicationFiled: January 7, 2022Publication date: July 28, 2022Applicant: Movidius Ltd.Inventors: Sam Caulfield, David Macdara Moloney, Gary Garfield Barrington Baugh
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Patent number: 11367246Abstract: A volumetric data structure models a particular volume representing the particular volume at a plurality of levels of detail. A first entry in the volumetric data structure includes a first set of bits representing voxels at a first level of detail, the first level of detail includes the lowest level of detail in the volumetric data structure, values of the first set of bits indicate whether a corresponding one of the voxels is at least partially occupied by respective geometry, where the volumetric data structure further includes a number of second entries representing voxels at a second level of detail higher than the first level of detail, the voxels at the second level of detail represent subvolumes of volumes represented by voxels at the first level of detail, and the number of second entries corresponds to a number of bits in the first set of bits with values indicating that a corresponding voxel volume is occupied.Type: GrantFiled: August 19, 2017Date of Patent: June 21, 2022Assignee: MOVIDIUS LTD.Inventors: David Macdara Moloney, Jonathan David Byrne
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Publication number: 20220148251Abstract: A view of geometry captured in image data generated by an imaging sensor is compared with a description of the geometry in a volumetric data structure. The volumetric data structure describes the volume at a plurality of levels of detail and includes entries describing voxels defining subvolumes of the volume at multiple levels of detail. The volumetric data structure includes a first entry to describe voxels at a lowest one of the levels of detail and further includes a number of second entries to describe voxels at a higher, second level of detail, the voxels at the second level of detail representing subvolumes of the voxels at the first level of detail. Each of these entries include bits to indicate whether a corresponding one of the voxels is at least partially occupied with the geometry. One or more of these entries are used in the comparison with the image data.Type: ApplicationFiled: June 14, 2021Publication date: May 12, 2022Applicant: Movidius Ltd.Inventors: David Macdara Moloney, Jonathan David Byrne
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Patent number: 11222459Abstract: A ray is cast into a volume described by a volumetric data structure, which describes the volume at a plurality of levels of detail. A first entry in the volumetric data structure includes a first set of bits representing voxels at a lowest one of the plurality of levels of detail, and values of the first set of bits indicate whether a corresponding one of the voxels is at least partially occupied by respective geometry. A set of second entries in the volumetric data structure describe voxels at a second level of detail, which represent subvolumes of the voxels at the first lowest level of detail. The ray is determined to pass through a particular subset of the voxels at the first level of detail and at least a particular one of the particular subset of voxels is determined to be occupied by geometry.Type: GrantFiled: August 14, 2020Date of Patent: January 11, 2022Assignee: Movidius Ltd.Inventors: Sam Caulfield, David Macdara Moloney, Gary Garfield Barrington Baugh
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Publication number: 20210390376Abstract: A grammar is used in a grammatical evolution of a set of parent neural network models to generate a set of child neural network models. A generation of neural network models is tested based on a set of test data, where the generation includes the set of child neural network models. Respective values for each one of a plurality of attributes are determined for each neural network in the generation, where one of the attributes includes a validation accuracy value determined from the test. Multi-objective optimization is performed based on the values of the plurality of attributes for the generation of neural networks and a subset of the generation of neural network models is selected based on the results of the multi-objective optimization.Type: ApplicationFiled: October 31, 2019Publication date: December 16, 2021Applicant: Movidius Ltd.Inventors: Jonathan David Byrne, David Macdara Moloney, Xiaofan Xu, Tomaso F L Cetto
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Publication number: 20210213973Abstract: A raycaster performs a raycasting algorithm, where the raycasting algorithm takes, as an input, a sparse hierarchical volumetric data structure. Performing the raycasting algorithm includes casting a plurality of rays from a reference point into the 3D volume, and, for each of the plurality of rays, traversing the ray to determine whether voxels in the set of voxels are intersected by the ray and are occupied, where the ray is to be traversed according to an approximate traversal algorithm.Type: ApplicationFiled: August 29, 2019Publication date: July 15, 2021Applicant: Movidius Ltd.Inventors: Dexmont Alejandro Carillo Peña, Luis Manuel Rodríguez Martín de la Sierra, Carlos Marquez Rodriguez-Peral, Luca Sarti, David Macdara Moloney, Sam Caulfield, Jonathan David Byrne
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Publication number: 20210201526Abstract: A machine learning system is provided to enhance various aspects of machine learning models. In some aspects, a substantially photorealistic three-dimensional (3D) graphical model of an object is accessed and a set of training images of the 3D graphical mode are generated, the set of training images generated to add imperfections and degrade photorealistic quality of the training images. The set of training images are provided as training data to train an artificial neural network.Type: ApplicationFiled: May 21, 2019Publication date: July 1, 2021Applicant: Movidius Ltd.Inventors: David Macdara Moloney, Jonathan David Byrne, Léonie Raideen Buckley, Xiaofan Xu, Dexmont Alejandro Peña Carillo, Luis M. Rodríguez Martín de la Sierra, Carlos Márquez Rodríguez-Peral, Mi Sun Park, Cormac M. Brick, Alessandro Palla
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Patent number: 11037361Abstract: A view of geometry captured in image data generated by an imaging sensor is compared with a description of the geometry in a volumetric data structure. The volumetric data structure describes the volume at a plurality of levels of detail and includes entries describing voxels defining subvolumes of the volume at multiple levels of detail. The volumetric data structure includes a first entry to describe voxels at a lowest one of the levels of detail and further includes a number of second entries to describe voxels at a higher, second level of detail, the voxels at the second level of detail representing subvolumes of the voxels at the first level of detail. Each of these entries include bits to indicate whether a corresponding one of the voxels is at least partially occupied with the geometry. One or more of these entries are used in the comparison with the image data.Type: GrantFiled: August 19, 2017Date of Patent: June 15, 2021Assignee: Movidius Ltd.Inventors: David Macdara Moloney, Jonathan David Byrne
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Publication number: 20210166464Abstract: A particular voxel is identified within a volume and a hash table is used to obtain volumetric data describing the particular voxel within the volume. Values of x-, y- and z-coordinates in the volume associated with the particular voxel are determined an index value associated with the particular voxel is determined according to a hashing algorithm, where the index value is determined from summing weighted values of the x-, y- and z-coordinates, and the weighted values are based on a variable value corresponding to a dimension of the volume. A particular entry is identified in the hash table based on the index value, where the particular entry includes volumetric data, and the volumetric data identifies, for the particular voxel, whether the particular voxel is occupied.Type: ApplicationFiled: October 16, 2018Publication date: June 3, 2021Applicant: Movidius Ltd.Inventors: David Macdara Moloney, Jonathan David Byrne, Leonie Buckley, Gary Garfield Barrington Baugh, Sam Caulfield, Alessandro Palla, Ananya Gupta