Patents Examined by Vikkram Bali
  • Patent number: 11514702
    Abstract: Systems and methods for identifying landmarks of a document from a digital representation of the document. The method comprises accessing the digital representation of the document and operating a Machine Learning Algorithm (MLA), the MLA having been trained based on a set of training digital representations of documents associated with labels. The operating the MLA comprises down-sampling the digital representation of the document, detecting landmarks, generating fractional pixel coordinates for the detected landmarks. The method further determines the pixel coordinates of the landmarks by upscaling the fractional pixel coordinates from the second resolution to the first resolution and outputs the pixel coordinates of the landmarks.
    Type: Grant
    Filed: January 31, 2020
    Date of Patent: November 29, 2022
    Inventors: Patrick Steeves, Ying Zhang
  • Patent number: 11514315
    Abstract: A deep neural network training method and apparatus and a computer device are provided. The deep neural network training method includes: obtaining task attributes of nodes in a current network layer in a tree-like network topology (S101); performing cluster analysis on the nodes in the current network layer based on the task attributes of the nodes in the current network layer and extracting a common part of task attributes of multiple nodes in a same category as a task attribute for a parent node of the multiple nodes (S102); training a network parameter of each parent node based on a task attribute of this parent node (S103); and determining that training of a deep neural network corresponding to the tree-like network topology is completed, after completion of training of all nodes in all network layers (S104). The operation efficiency of deep learning can be improved through this solution.
    Type: Grant
    Filed: December 7, 2018
    Date of Patent: November 29, 2022
    Inventors: Di Xie, Shiliang Pu
  • Patent number: 11514668
    Abstract: A method for situation awareness is provided. The method comprises: preparing a neural network trained by a learning set, wherein the learning set includes a plurality of maritime images and maritime information including object type information which includes a first type index for a vessel, a second type index for a water surface and a third type index for a ground surface, and distance level information which includes a first level index indicating that a distance is undefined, a second level index indicating a first distance range and a third level index indicating a second distance range greater than the first distance range; obtaining a target maritime image generated from a camera; and determining a distance of a target vessel based on the distance level index of the maritime information being outputted from the neural network which receives the target maritime image and having the first type index.
    Type: Grant
    Filed: September 2, 2020
    Date of Patent: November 29, 2022
    Assignee: SEADRONIX CORP.
    Inventors: Byeol Teo Park, Han Keun Kim, Dong Hoon Kim
  • Patent number: 11499907
    Abstract: Systems and methods are provided for counting particles in a fluid flow. In an aspect, coordinates of particles are obtained from video data of particles in a fluid, the video data made up of a sequence of image frames. The particle positions are linked in each pair of consecutive image frames of the video data. The linked particle positions are used to calculate particle trajectories through sequential image frames of the video data, and the particles are counted based on the particle trajectory. In another aspect, the particle positions within each image frame are transformed to estimated positions within a common coordinate frame. The estimated particle positions of a particle are grouped into a cluster center, and the particle count is calculated based on the cluster centers.
    Type: Grant
    Filed: June 11, 2018
    Date of Patent: November 15, 2022
    Assignee: miDiagnostics NV
    Inventors: Rene Vidal, Benjamin D. Haeffele, Florence Yellin
  • Patent number: 11495021
    Abstract: A picture annotation method, includes: converting, into a video image, multiple pictures in a set of pictures to be annotated; performing video annotation on the video image to obtain an annotation result; and using the obtained annotation result as an annotation result of each picture in the set of pictures to be annotated according to a correspondence between a video frame in the video image and a picture in the set of pictures to be annotated.
    Type: Grant
    Filed: June 28, 2021
    Date of Patent: November 8, 2022
    Assignee: Alipay (Hangzhou) Information Technology Co., Ltd.
    Inventor: Xi Zhou
  • Patent number: 11488320
    Abstract: A pose estimation method includes obtains an event stream from an event-based vision sensor configured to capture a target object to which light-emitting devices flickering at a predetermined first frequency are attached, obtains a polarity change period of at least one pixel based on the event stream, generates an image frame sequence using at least one target pixel having a polarity change period corresponding to the first frequency, among the at least one pixel, extracts a feature sequence including feature vectors corresponding to the at least one target pixel, from the image frame sequence, and estimates a pose sequence of the target object by applying the feature sequence to a deep neural network (DNN) model.
    Type: Grant
    Filed: July 30, 2020
    Date of Patent: November 1, 2022
    Assignee: Samsung Electronics Co., Ltd.
    Inventors: Huiguang Yang, Jiguang Xue, Zhuo Li, Chuangqi Tang, Xiongzhan Linghu, Yuguang Li, Liu Yang, Jian Zhao, Manjun Yan
  • Patent number: 11478226
    Abstract: An exemplary system, method and computer-accessible medium for detecting an anomaly(ies) in an anatomical structure(s) of a patient(s) can be provided, which can include, for example, receiving imaging information related to the anatomical structure(s) of the patient(s), classifying a feature(s) of the anatomical structure(s) based on the imaging information using a neural network (s), and detecting the anomaly(ies) based on data generated using the classification procedure. The imaging information can include at least three images of the anatomical structure(s).
    Type: Grant
    Filed: January 19, 2018
    Date of Patent: October 25, 2022
    Assignees: New York University, Yeda Research And Development Co., Ltd.
    Inventors: Itay Kezurer, Achiau Ludomirsky, Yaron Lipman
  • Patent number: 11475682
    Abstract: A method for controlling a movable object includes detecting a live object within a proximity of the movable object, determining an operation mode to operate the movable object with the live object detected within the proximity of the movable object, and applying a control scheme associated with the operation mode to control an operation of the movable object.
    Type: Grant
    Filed: March 19, 2019
    Date of Patent: October 18, 2022
    Inventors: You Zhou, Shaojie Shen, Jiexi Du, Guyue Zhou
  • Patent number: 11461888
    Abstract: The disclosure provides a method and an image processor for computing decay factors for display degradation compensation. The method includes the following steps. A sequence of frames including a current frame are received. Whether the current frame is a dynamic frame or a static frame is determined. When the current frame is the dynamic frame, accumulation on decay factors is performed. When the current frame is the static frame, accumulation on the decay factors is not performed.
    Type: Grant
    Filed: July 20, 2020
    Date of Patent: October 4, 2022
    Assignee: Novatek Microelectronics Corp.
    Inventors: Li-Chieh Chen, Yen-Tao Liao
  • Patent number: 11455735
    Abstract: The present disclosure relates to a target tracking method, device, system, and a non-transitory computer-readable storage medium. The method includes: determining an area where a current target is located by performing target detection on a current frame image; extracting a current position information of the area where the current target is located; predicting a position information of an area where each historical target is located at a corresponding moment of the current frame image based on historical position information of an area where each historical target is located in one or more historical frame images; determining a historical target that is the same target as the current target based on a position difference between the current position information and the predicted position information, and tracking the current target.
    Type: Grant
    Filed: June 29, 2020
    Date of Patent: September 27, 2022
    Inventors: Yuhai Sun, Yu Gu, Jiashuang Zong
  • Patent number: 11449716
    Abstract: Methods and systems for training a model labeling two or more organic structures in an image. One method includes receiving a set of training images including a first plurality of images and a second plurality of images. Each of the first plurality of images including a label for a first subset of the two or more organic structures and each of the second plurality of images including a label for a second subset of the two or more organic structures, the second subset being different than the first subset. The method also includes training the model using the first plurality of images, the second plurality of images, and a label merging function mapping a label included in the first plurality of images to a label included in the second plurality of images.
    Type: Grant
    Filed: March 31, 2020
    Date of Patent: September 20, 2022
    Inventors: Hongzhi Wang, Tanveer Fathima Syeda-Mahmood, John Paul Francis
  • Patent number: 11443138
    Abstract: A virtual camera configuration system includes any number of cameras disposed about an area, such as an event venue. The system also includes at least one processor and at least one non-transitory, computer-readable medium communicatively coupled to the at least one processor. In certain embodiments, the at least one non-transitory, computer-readable medium is configured to store instructions which, when executed, cause the processor to perform operations including receiving a set of game data, receiving a set of audiovisual data, and receiving a set of camera presets. The operations also include generating a set of training data and training a model based on the set of training data. The operations also include generating, using the model on a second set of game data and a second set of audiovisual data, a second set of camera presets associated with the set of virtual cameras.
    Type: Grant
    Filed: May 7, 2020
    Date of Patent: September 13, 2022
    Assignee: Intel Corporation
    Inventors: Fai Yeung, Vasanthi Jangala Naga, Gilson Goncalves de Lima, Patrick Youngung Shon, Yogeshwara Krishnan
  • Patent number: 11429811
    Abstract: A method includes passing an original text document through distortion filter generators to generate a training dataset that includes distorted text documents. Each distortion filter generator is configured to distort words or letters of words in phrases of text of a facsimile image in a respective unique manner. A neural network model is trained to recognize each respective distortion and match each respective distortion with each respective distortion filter generator based on the training dataset and the original text document. Image data of one facsimile having at least one text distortion is received and inputted to the trained neural network model. The output of the trained neural network model is coupled to an input of an optical character recognition (OCR) engine. The trained neural network model and the OCR engine convert the received image data of the incoming facsimile corrected for the at least one text distortion to machine-encoded text.
    Type: Grant
    Filed: February 10, 2020
    Date of Patent: August 30, 2022
    Assignee: Capital One Services, LLC
    Inventors: Reza Farivar, Jeremy Goodsitt, Vincent Pham, Austin Walters, Fardin Abdi Taghi Abad, Anh Truong, Mark Watson
  • Patent number: 11430136
    Abstract: Methods, apparatus, systems and articles of manufacture to improve efficiency of object tracking in video frames are disclosed. An example apparatus includes a clusterer to cluster a map of a video frame into blobs; a comparator to determine an intersection over union value between the blobs and bounding boxes in a second video frame; and an interface to initiate object detection by a neural network on the first video frame when the intersection over union does not satisfy a threshold.
    Type: Grant
    Filed: December 19, 2019
    Date of Patent: August 30, 2022
    Assignee: Intel Corporation
    Inventors: Srenivas Varadarajan, Girish Srinivasa Murthy, Anand Bodas, Omesh Tickoo, Vallabhajosyula Somayazulu
  • Patent number: 11428959
    Abstract: Disclosed is a method for determining a subject's reference head posture, the method including: a) obtaining a movement or a position of at least one eyelid of the subject while he/she moves his/her head up and down starting from an initial head posture wherein he/she directs his/her gaze towards a predetermined direction, the subject keeping his/her gaze directed towards the predetermined direction during the motion of his/her head; and b) determining the reference head posture as a function of a movement or a position of at least one eyelid of the subject during the motion of his/her head at step a). Further disclosed is a method for measuring a distinctive height associated with a frame of a pair of spectacles worn by the subject, as well as a method for mounting and for verifying the mounting of an ophthalmic lens in a frame of a pair of spectacles.
    Type: Grant
    Filed: December 3, 2018
    Date of Patent: August 30, 2022
    Assignee: Essilor International
    Inventor: Gilles Le Saux
  • Patent number: 11417150
    Abstract: The information processing apparatus (2000) of the example embodiment 1 includes an acquisition unit (2020), a clustering unit (2040), and a modeling unit (2060). The acquisition unit (2020) acquires a plurality of trajectory data. Until a predetermined termination condition is satisfied, the clustering unit (2040) repeatedly performs: 1) dividing the plurality of trajectory data into one or more groups using a group identity distribution of each trajectory data; 2) determining a time-sequence of representative velocity for each group; 3) determining, for each trajectory data, a time-sequence of a latent position distribution of a corresponding object; and 4) determining a scaling factor for each trajectory data; and 5) updating the group identity distribution of each trajectory data. The modeling unit (2060) generates a model data for each group. The model data includes the time-sequence of representative velocity generated by the clustering unit (2040).
    Type: Grant
    Filed: December 28, 2017
    Date of Patent: August 16, 2022
    Inventor: Devendra Dhaka
  • Patent number: 11386564
    Abstract: A method, a system, and a computer-accessible recording medium for motion recognition based on an atomic pose are provided. A video frame including a live body is obtained. An atomic pose feature value is generated by analyzing the live body in the video frame. A hash value of the atomic pose is generated by executing a hash function according to the atomic pose feature value. The live body executing a specific motion is recognized by comparing the atomic pose hash value.
    Type: Grant
    Filed: February 12, 2020
    Date of Patent: July 12, 2022
    Assignee: Wistron Corporation
    Inventor: Yi-Hsi Huang
  • Patent number: 11379719
    Abstract: A method of tracking an object across a stream of images comprises determining a region of interest (ROI) bounding the object in an initial frame of an image stream. A HOG map is provided for the ROI by: dividing the ROI into an array of M×N cells, each cell comprising a plurality of image pixels; and determining a HOG for each of the cells. The HOG map is stored as indicative of the features of the object. Subsequent frames are acquired from the stream of images. The frames are scanned ROI by ROI to identify a candidate ROI having a HOG map best matching the stored HOG map features. If the match meets a threshold, the stored HOG map indicative of the features of the object is updated according to the HOG map for the best matching candidate ROI.
    Type: Grant
    Filed: January 17, 2020
    Date of Patent: July 5, 2022
    Assignee: FotoNation Limited
    Inventors: Dragos Dinu, Mihai Constantin Munteanu, Alexandru Caliman
  • Patent number: 11361449
    Abstract: A method for multi-object tracking includes receiving a sequence of images generated at respective times by one or more sensors configured to sense an environment through which objects are moving relative to the one or more sensors, and constructing a message passing graph in which each of a multiplicity of layers corresponds to a respective one in the sequence of images. The method also includes tracking multiple features through the sequence of images, including passing messages in a forward direction and a backward direction through the message passing graph to share information across time.
    Type: Grant
    Filed: September 4, 2020
    Date of Patent: June 14, 2022
    Assignee: Luminar, LLC
    Inventors: Vahid R. Ramezani, Akshay Rangesh, Benjamin Englard, Siddhesh S. Mhatre, Meseret R. Gebre, Pranav Maheshwari
  • Patent number: 11348236
    Abstract: A processor receives an image of a syringe. After identifying a background and foreground of the image, where the foreground indicates pixels that may be associated with a defect, the processor subtracts the background to generate an updated image with an accentuated foreground. The processor applies a bounding box to a group of pixels in the foreground and inputs the bounding box into a classifier. The classifier outputs a label indicating whether the syringe is defective.
    Type: Grant
    Filed: April 10, 2020
    Date of Patent: May 31, 2022
    Assignee: Landing AI
    Inventors: Wei Fu, Rahul Devraj Solanki, Mark William Sabini, Yuanzhe Dong, Hao Sheng, Gopi Prashanth Gopal, Ankur Rawat, Sanjeev Satheesh