Patents Examined by Samir Ahmed
  • Patent number: 10592775
    Abstract: An image processing method includes steps of receiving an image sequence; when at least one object appears in the image sequence, analyzing a moving trajectory of each object; extracting at least one characteristic point from each moving trajectory; classifying the at least one characteristic point of each moving trajectory within a predetermined time period into at least one cluster; and storing at least one characteristic parameter of each cluster.
    Type: Grant
    Filed: September 4, 2017
    Date of Patent: March 17, 2020
    Assignee: VIVOTEK INC.
    Inventors: Cheng-Chieh Liu, Chih-Yen Lin
  • Patent number: 10586098
    Abstract: The method according to the invention is based on a first image of a first eye region of a person and a second image of a second eye region of the person, wherein the first eye region contains one of the eyes of the person, for example the right eye, and the second eye region contains the other eye of the person, for example the left eye; one of the images is mirrored, and the mirrored and the non-mirrored image are combined in the position space and/or in the feature space, in order to generate a template of an overlaid image. The template contains biometric features for person recognition.
    Type: Grant
    Filed: October 18, 2017
    Date of Patent: March 10, 2020
    Assignee: BIOID AG
    Inventors: Robert Frischholz, Hagen Zurek
  • Patent number: 10586310
    Abstract: Supervised machine learning using neural networks is applied to denoising images rendered by MC path tracing. Specialization of neural networks may be achieved by using a modular design that allows reusing trained components in different networks and facilitates easy debugging and incremental building of complex structures. Specialization may also be achieved by using progressive neural networks. In some embodiments, training of a neural-network based denoiser may use importance sampling, where more challenging patches or patches including areas of particular interests within a training dataset are selected with higher probabilities than others. In some other embodiments, generative adversarial networks (GANs) may be used for training a machine-learning based denoiser as an alternative to using pre-defined loss functions.
    Type: Grant
    Filed: April 5, 2018
    Date of Patent: March 10, 2020
    Assignees: Pixar, Disney Enterprises
    Inventors: Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer, Jan Novak
  • Patent number: 10578672
    Abstract: A digital circuit includes a scan chain which loads data into and unloads data from the digital circuit. Checking circuitry is coupled to the scan chain and generates a first digital signature based on data indicative of a pre-testing status of the digital circuit as the data is unloaded from the digital circuit via the scan chain. When testing is completed, the data is restored to the digital circuit via the scan chain. The checking circuitry generates a second digital signature as the data is loaded into the digital circuit. The first digital signature is compared to the second digital signature to verify an integrity of the process. A specific data pattern may be loaded into the scan chain as the data is unloaded. An output of the scan chain may be monitored to detect the pattern and an error signal may be generated based on when the pattern is detected.
    Type: Grant
    Filed: December 31, 2015
    Date of Patent: March 3, 2020
    Assignee: STMICROELECTRONICS (GRENOBLE 2) SAS
    Inventors: David Jacquet, Didier Fuin
  • Patent number: 10572725
    Abstract: Field extraction from a form image includes identifying a target field of the form image, defining a patch from the form image based on the target field, and encoding the patch using a color encoding scheme to obtain an encoded patch. Field extraction further includes applying a trained classifier to the encoded patch to identify a relationship between a field value and a field identifier, and extracting the field value from the form image according to the relationship.
    Type: Grant
    Filed: March 30, 2018
    Date of Patent: February 25, 2020
    Assignee: Intuit Inc.
    Inventors: Richard Becker, Kimia Hassanzadeh
  • Patent number: 10572979
    Abstract: Supervised machine learning using neural networks is applied to denoising images rendered by MC path tracing. Specialization of neural networks may be achieved by using a modular design that allows reusing trained components in different networks and facilitates easy debugging and incremental building of complex structures. Specialization may also be achieved by using progressive neural networks. In some embodiments, training of a neural-network based denoiser may use importance sampling, where more challenging patches or patches including areas of particular interests within a training dataset are selected with higher probabilities than others. In some other embodiments, generative adversarial networks (GANs) may be used for training a machine-learning based denoiser as an alternative to using pre-defined loss functions.
    Type: Grant
    Filed: April 5, 2018
    Date of Patent: February 25, 2020
    Assignees: Pixar, Disney Enterprises, Inc.
    Inventors: Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer, Jan Novak
  • Patent number: 10573017
    Abstract: A depth estimation method and a depth estimation apparatus of multi-view images where the method includes: taking each image among a plurality of images in a same scenario as a current image to perform the processing of: obtaining an initial depth value of each pixel in the current image; dividing the current image into a plurality of superpixels; obtaining plane parameters of the plurality of superpixels according to a predetermined constraint condition based on the initial depth values; and generating a depth value of each pixel in the superpixels based on the plane parameters of the superpixels; wherein the predetermined constraint condition includes: a co-connection constraint, which is related to a difference between depth values of adjacent points on neighboring superpixels that do not occlude each other.
    Type: Grant
    Filed: December 29, 2017
    Date of Patent: February 25, 2020
    Assignee: FUJITSU LIMITED
    Inventors: Hu Tian, Fei Li
  • Patent number: 10572976
    Abstract: A system and method to enhance observation resolution using continuous learning include obtaining a first image of a surface area from a first satellite, and obtaining a second image of the surface area from a second satellite. The first image has a lower spatial resolution than the second image, and temporal resolution of the first images obtained by the first satellite is higher than temporal resolution of the second images obtained by the second satellite. The method also includes determining a convolution matrix A or training a neural network, obtaining additional one or more of the first images prior to obtaining an additional one of the second images, and generating a new image from each of the one or more of the first images using the convolution matrix A or the neural network. The new image has a higher spatial resolution than the one or more of the first images.
    Type: Grant
    Filed: October 18, 2017
    Date of Patent: February 25, 2020
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Conrad M. Albrecht, Hendrik F. Hamann, Siyuan Lu, Sharathchandra U. Pankanti
  • Patent number: 10564108
    Abstract: A system and method for inspecting a composite material structure for defects includes a) an inspection apparatus having a heating device for heating a surface of the structure, an infrared camera for receiving radiation from the surface in response to heating, a controller configured to generate thermal images from the infrared radiation, b) a training system includes an arrangement for obtaining thermal images from a known composite material sample including a plurality of heating elements positioned to apply heat to an entire surface of the sample, an infrared camera for capturing thermal images of the sample, and a processing system for recording the thermal images in a training database, and c) a computer system coupled to the training system and the inspection apparatus adapted to receive thermal images from the inspection apparatus and detect parameters of defects in the structure using the training database.
    Type: Grant
    Filed: July 3, 2017
    Date of Patent: February 18, 2020
    Assignee: Saudi Arabian Oil Company
    Inventor: Ahmed S. Al-Omari
  • Patent number: 10567753
    Abstract: Various techniques and tools for encoding and decoding (e.g., in a video encoder/decoder) binary information (e.g., skipped macroblock information) are described. In some embodiments, the binary information is arranged in a bit plane, and the bit plane is coded at the picture/frame layer. The encoder and decoder process the binary information and, in some embodiments, switch coding modes. For example, the encoder and decoder use normal, row-skip, column-skip, or differential modes, or other and/or additional modes. In some embodiments, the encoder and decoder define a skipped macroblock as a predicted macroblock whose motion is equal to its causally predicted motion and which has zero residual error. In some embodiments, the encoder and decoder use a raw coding mode to allow for low-latency applications.
    Type: Grant
    Filed: July 2, 2019
    Date of Patent: February 18, 2020
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Sridhar Srinivasan, Pohsiang Hsu
  • Patent number: 10558895
    Abstract: Techniques for generating 3D gaze predictions based on a deep learning system are described. In an example, the deep learning system includes a neural network. A scaled image is generated from 2D image showing a user face based on a rough distance between the user eyes and a camera that generated the 2D image. Image crops at different resolutions are generated from the scaled image and include a crop around each of the user eyes and a crop around the user face. These crops are input to the neural network. In response, the neural network outputs a distance correction and a 2D gaze vector per user eye. A corrected eye-to-camera distance is generated by correcting the rough distance based on the distance correction. A 3D gaze vector for each of the user eyes is generated based on the corresponding 2D gaze vector and the corrected distance.
    Type: Grant
    Filed: March 30, 2018
    Date of Patent: February 11, 2020
    Assignee: Tobii AB
    Inventor: Erik Linden
  • Patent number: 10560216
    Abstract: Fifth Generation (5G) or pre-5G communication system for supporting a data transfer rate higher than that of a fourth Generation (4G) communication system, such as Long Term Evolution (LTE), and subsequent systems. The present disclosure provides a method for transmitting a signal by a transmission terminal in a communication system using a Low Density Parity Check (LDPC) code. The method include receiving a change request for changing a coding rate of the LDPC code, from a reception terminal; determining a first coding rate based on the change request; and transmitting information on the first coding rate in respond to the change request, to a reception terminal, wherein the change request for changing the coding rate comprises at least one of information indicating a coding rate determined by the reception terminal, or information indicating a state of the reception terminal.
    Type: Grant
    Filed: January 12, 2017
    Date of Patent: February 11, 2020
    Assignee: Samsung Electronics Co., Ltd.
    Inventors: Chi-Woo Lim, Jae-Yoel Kim, Woo-Myoung Park, Seok-Ki Ahn, Min Jang
  • Patent number: 10558887
    Abstract: In implementations of digital image search based on arbitrary image features, a server computing device maintains an images database of digital images, and includes an image search system that receives a search input as a digital image depicting image features, and receives search criteria of depicted image features in the digital image. The image search system can then determine similar images to the received digital image based on similarity criterion corresponding to the search criteria. A trained image model of the image search system is applied to determine an image feature representation of the received digital image. A feature mask model of the image search system is applied to the image feature representation to determine a masked feature representation of the received digital image. The masked feature representation of the received digital image is compared to a masked feature representation of each respective database image to identify the similar images.
    Type: Grant
    Filed: December 4, 2017
    Date of Patent: February 11, 2020
    Assignee: Adobe Inc.
    Inventors: Shagun Sodhani, Nikaash Puri
  • Patent number: 10558892
    Abstract: Embodiments of the invention provide a method for scene understanding based on a sequence of image frames. The method comprises converting each pixel of each image frame to neural spikes, and extracting features from the sequence of image frames by processing neural spikes corresponding to pixels of the sequence of image frames. The method further comprises encoding the extracted features as neural spikes, and classifying the extracted features.
    Type: Grant
    Filed: September 28, 2018
    Date of Patent: February 11, 2020
    Assignee: International Business Machines Corporation
    Inventors: Alexander Andreopoulos, Rathinakumar Appuswamy, Pallab Datta, Steven K. Esser, Dharmendra S. Modha
  • Patent number: 10552661
    Abstract: Embodiments of an automated method of processing fingerprint images, identity information is extracted from prints typically classified as having “no identification value” because of sparse or missing minutiae by capturing ridge contour information. Bezier approximations of ridge curvature are used as Ridge Specific Markers. Control points arising from Bezier curves generate unique polygons that represent the actual curve in the fingerprint. The Bezier-based descriptors are then grouped together and compared to corresponding reference print Ridge Specific Marker data. The method makes it possible to fuse a plurality of individual latent print portions into a single descriptor of identity and use the resulting data for comparison and identification. Processing of poor quality reference prints according to the methods disclosed renders these prints useable for reference purposes.
    Type: Grant
    Filed: February 6, 2012
    Date of Patent: February 4, 2020
    Assignee: SCIOMETRICS, LLC
    Inventors: Mark Anthony Walch, Donald T. Gantz, Daniel Thomas Gantz
  • Patent number: 10555264
    Abstract: A method for detecting control information in a wireless communication system is provided. The method includes checking a cyclic redundancy check (CRC) error by monitoring control channels, determining whether a value of an error check field is equal to a specific value, and, if the value of the error check field is equal to a specific value, detecting the control information on the control channel.
    Type: Grant
    Filed: September 28, 2016
    Date of Patent: February 4, 2020
    Assignee: LG Electronics Inc.
    Inventors: Jae Hoon Chung, So Yeon Kim, Jong Min Kim, Doo Hyun Sung
  • Patent number: 10546183
    Abstract: A liveness detection system comprises a controller, a video input, a feature recognition module, and a liveness detection module. The controller is configured to control an output device to provide randomized outputs to an entity over an interval of time. The video input is configured to receive a moving image of the entity captured by a camera over the interval of time. The feature recognition module is configured to process the moving image to detect at least one human feature of the entity. The liveness detection module is configured to compare with the randomized outputs a behaviour exhibited by the detected human feature over the interval of time to determine whether the behaviour is an expected reaction to the randomized outputs, thereby determining whether the entity is a living being.
    Type: Grant
    Filed: February 9, 2018
    Date of Patent: January 28, 2020
    Assignee: Yoti Holding Limited
    Inventors: Francisco Angel Garcia Rodriguez, Benjamin Robert Tremoulheac, Symeon Nikitidis, Thomas Bastiani, Miguel Jimenez
  • Patent number: 10547328
    Abstract: Systems, methods, and apparatus are provided for iteratively decoding a codeword. Once a codeword is received, the codeword is processed to generate an incremental hard decision value and a log likelihood ratio amplitude value. These values are generated by processing the codeword using a soft output Viterbi algorithm. A faulty symbol in the codeword is identified. A complete hard decision value is generated using the incremental hard decision value. The LLR amplitude value and complete hard decision value corresponding to the identified faulty symbol are selectively provided to a decoder and the decoder uses these values to decode the codeword.
    Type: Grant
    Filed: November 18, 2014
    Date of Patent: January 28, 2020
    Assignee: Marvell International Ltd.
    Inventors: Shu Li, Yifei Zhang, Wei Cao
  • Patent number: 10534982
    Abstract: Techniques for generating 3D gaze predictions based on a deep learning system are described. In an example, the deep learning system includes a neural network. The neural network is trained with training images. During the training, calibration parameters are initialized and input to the neural network, and are updated through the training. Accordingly, the network parameters of the neural network are updated based in part on the calibration parameters. Upon completion of the training, the neural network is calibrated for a user. This calibration includes initializing and inputting the calibration parameters along with calibration images showing an eye of the user to the neural network. The calibration includes updating the calibration parameters without changing the network parameters by minimizing the loss function of the neural network based on the calibration images. Upon completion of the calibration, the neural network is used to generate 3D gaze information for the user.
    Type: Grant
    Filed: March 30, 2018
    Date of Patent: January 14, 2020
    Assignee: Tobii AB
    Inventor: Erik Linden
  • Patent number: 10532432
    Abstract: Quality judgment on a laser beam intensity distribution is performed by taking an observation condition of the laser beam into consideration. A machine learning device includes: a state observing means that acquires data indicating an intensity distribution of a laser beam and data indicating a condition for observing the laser beam, performed to generate the data indicating the intensity distribution as input data; a label acquisition means that acquires an evaluation value related to judgment of the quality of the laser beam as a label; and a learning means that performs supervised learning using a pair of the input data acquired by the state observing means and the label acquired by the label acquisition means as training data to construct a learning model for judging the quality of the laser beam.
    Type: Grant
    Filed: July 31, 2018
    Date of Patent: January 14, 2020
    Assignee: Fanuc Corporation
    Inventor: Yoshitaka Kubo