Patents by Inventor Robert R. Price

Robert R. Price 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).

  • Publication number: 20240281431
    Abstract: A method of labeling training data includes inputting a plurality of unlabeled input data samples into each of a plurality of pre-trained neural networks and extracting a set of feature embeddings from multiple layer depths of each of the plurality of pre-trained neural networks. The method also includes generating a plurality of clusterings from the set of feature embeddings. The method also includes analyzing, by a processing device, the plurality of clusterings to identify a subset of the plurality of unlabeled input data samples that belong to a same unknown class. The method also includes assigning pseudo-labels to the subset of the plurality of unlabeled input data samples.
    Type: Application
    Filed: April 26, 2024
    Publication date: August 22, 2024
    Inventors: Matthew Shreve, Francisco E. Torres, Raja Bala, Robert R. Price, Pei Li
  • Publication number: 20240265717
    Abstract: A system and method for robust estimation of state parameters from internal readings in a sequence of images are provided. Various techniques can be implemented to address observation noise and/or underlying process noise to stabilize the readings.
    Type: Application
    Filed: February 3, 2023
    Publication date: August 8, 2024
    Applicant: Palo Alto Research Center Incorporated
    Inventor: Robert R. Price
  • Publication number: 20240249476
    Abstract: A system captures, by a recording device, a scene with physical objects, the scene displayed as a three-dimensional (3D) mesh. The system marks 3D annotations for a physical object and identifies a mask. The mask indicates background pixels corresponding to a region behind the physical object. Each background pixel is associated with a value. The system captures a plurality of images of the scene with varying features, wherein a respective image includes: two-dimensional (2D) projections corresponding to the marked 3D annotations for the physical object; and the mask based on the associated value for each background pixel. The system updates the value of each background pixel with a new value. The system trains a machine model using the respective image as generated labeled data, thereby obtaining the generated labeled data in an automated manner based on a minimal amount of marked annotations.
    Type: Application
    Filed: January 19, 2023
    Publication date: July 25, 2024
    Applicant: Palo Alto Research Center Incorporated
    Inventors: Matthew A. Shreve, Robert R. Price
  • Patent number: 12002265
    Abstract: A method includes defining a model for a liquid while the liquid is positioned at least partially within a nozzle of a printer. The method also includes synthesizing video frames of the liquid using the model to produce synthetic video frames. The method also includes generating a labeled dataset that includes the synthetic video frames and corresponding model values. The method also includes receiving real video frames of the liquid while the liquid is positioned at least partially within the nozzle of the printer. The method also includes generating an inverse mapping from the real video frames to predicted model values using the labeled dataset. The method also includes reconstructing the liquid in the real video frames based at least partially upon the predicted model values.
    Type: Grant
    Filed: June 24, 2021
    Date of Patent: June 4, 2024
    Assignee: XEROX CORPORATION
    Inventors: Robert R. Price, Raja Bala, Svyatoslav Korneev, Christoforos Somarakis, Matthew Shreve, Adrian Lew, Palghat Ramesh
  • Patent number: 11983171
    Abstract: A method of labeling a dataset includes inputting a testing set comprising a plurality of input data samples into a plurality of pre-trained machine learning models to generate a set of embeddings output by the plurality of pre-trained machine learning models. The method further includes performing an iterative cluster labeling algorithm that includes generating a plurality of clusterings from the set of embeddings, analyzing the plurality of clusterings to identify a target embedding with a highest duster quality, analyzing the target embedding to determine a compactness for each of the plurality of clusterings of the target embedding, and identifying a target cluster among the plurality of clusterings of the target embedding based on the compactness. The method further includes assigning pseudo-labels to the subset of the plurality of input data samples that are members of the target duster.
    Type: Grant
    Filed: July 7, 2023
    Date of Patent: May 14, 2024
    Assignee: Xerox Corporation
    Inventors: Matthew Shreve, Francisco E. Torres, Raja Bala, Robert R. Price, Pei Li
  • Patent number: 11978243
    Abstract: One embodiment provides a system that facilitates efficient collection of training data. During operation, the system obtains, by a recording device, a first image of a physical object in a scene which is associated with a three-dimensional (3D) world coordinate frame. The system marks, on the first image, a plurality of vertices associated with the physical object, wherein a vertex has 3D coordinates based on the 3D world coordinate frame. The system obtains a plurality of second images of the physical object in the scene while changing one or more characteristics of the scene. The system projects the marked vertices on to a respective second image to indicate a two-dimensional (2D) bounding area associated with the physical object.
    Type: Grant
    Filed: November 16, 2021
    Date of Patent: May 7, 2024
    Assignee: Xerox Corporation
    Inventors: Matthew A. Shreve, Sricharan Kallur Palli Kumar, Jin Sun, Gaurang R. Gavai, Robert R. Price, Hoda M. A. Eldardiry
  • Patent number: 11958112
    Abstract: A three-dimensional (3D) printer includes a nozzle and a camera configured to capture a real image or a real video of a liquid metal while the liquid metal is positioned at least partially within the nozzle. The 3D printer also includes a computing system configured to perform operations. The operations include generating a model of the liquid metal positioned at least partially within the nozzle. The operations also include generating a simulated image or a simulated video of the liquid metal positioned at least partially within the nozzle based at least partially upon the model. The operations also include generating a labeled dataset that comprises the simulated image or the simulated video and a first set of parameters. The operations also include reconstructing the liquid metal in the real image or the real video based at least partially upon the labeled dataset.
    Type: Grant
    Filed: June 24, 2021
    Date of Patent: April 16, 2024
    Assignee: XEROX CORPORATION
    Inventors: Robert R. Price, Raja Bala, Svyatoslav Korneev, Christoforos Somarakis, Matthew Shreve, Adrian Lew, Palghat Ramesh
  • Publication number: 20240087287
    Abstract: A system determines an input video and a first annotated image from the input video which identifies an object of interest. The system initiates a tracker based on the first annotated image and the input video. The tracker generates, based on the first annotated image and the input video, information including: a sliding window for false positives; a first set of unlabeled images from the input video; and at least two images with corresponding labeled states. A semi-supervised classifier classifies, based on the information, the first set of unlabeled images from the input video. If a first unlabeled image is classified as a false positive, the system reinitiates the tracker based on a second annotated image occurring in a frame prior to a frame with the false positive. The system generates an output video comprising the input video displayed with tracking on the object of interest.
    Type: Application
    Filed: September 8, 2022
    Publication date: March 14, 2024
    Applicant: Palo Alto Research Center Incorporated
    Inventors: Matthew A. Shreve, Robert R. Price, Jeyasri Subramanian, Sumeet Menon
  • Patent number: 11917289
    Abstract: A system is provided which obtains images of a physical object captured by an AR recording device in a 3D scene. The system measures a level of diversity of the obtained images, for a respective image, based on at least: a distance and angle; a lighting condition; and a percentage of occlusion. The system generates, based on the level of diversity, a first visualization of additional images to be captured by projecting, on a display of the recording device, first instructions for capturing the additional images using the AR recording device. The system trains a model based on the collected data. The system performs an error analysis on the collected data to estimate an error rate for each image of the collected data. The system generates, based on the error analysis, a second visualization of further images to be captured. The model is further trained based on the collected data.
    Type: Grant
    Filed: June 14, 2022
    Date of Patent: February 27, 2024
    Assignee: Xerox Corporation
    Inventors: Matthew A. Shreve, Robert R. Price
  • Publication number: 20240013374
    Abstract: A method and system are provided for an improved semantic segmentation using a multi-stream late fusion using pretrained encoders to encode disparate channels independently while also integrating selected image features at a more abstract level in order to provide improved localization and image classification.
    Type: Application
    Filed: July 8, 2022
    Publication date: January 11, 2024
    Applicant: Palo Alto Research Center Incorporated
    Inventor: Robert R. Price
  • Publication number: 20240012853
    Abstract: A system and method provide extractions of regions of interest from images hand annotated by reviewers by lifting annotations from images, filtering out text labels, reconstructing continuous closed boundaries, and marking the contained region.
    Type: Application
    Filed: July 8, 2022
    Publication date: January 11, 2024
    Applicant: Palo Alto Research Center Incorporated
    Inventors: Robert R. Price, Raja Bala
  • Publication number: 20230410277
    Abstract: Techniques for determining print quality for a 3D printer are disclosed. An example method includes obtaining an image of a stream of material jetted from a nozzle of the 3D printer, and binarizing the image to distinguish background features from foreground features contained in the image. The method also includes identifying elements of jetted material in the foreground features, and computing statistical data characterizing the identified elements. The method also includes generating a quality score of jetting quality based on the statistical data and controlling the 3D printer based on the quality score. The quality score indicates a degree to which the elements of jetted material form droplets of a same size, shape, alignment, and jetting frequency.
    Type: Application
    Filed: June 15, 2022
    Publication date: December 21, 2023
    Inventors: Christoforos Somarakis, Robert R. Price, Svyatoslav Korneev, Matt Patterson, Adrian Lew, Brendan Mcnamara, Eli Wilson
  • Publication number: 20230410278
    Abstract: Image processing techniques for determining print quality for a 3D printer are disclosed. An example method includes obtaining an image of material jetted from a nozzle of the 3D printer. The method also includes binarizing the image to distinguish background features from foreground features contained in the image. The method also includes determining, by a processing device, a jetting quality based on the binarized image.
    Type: Application
    Filed: June 15, 2022
    Publication date: December 21, 2023
    Inventors: Christoforos Somarakis, Robert R. Price, Svyatoslav Korneev, Matt Patterson, Adrian Lew, Brendan Mcnamara, Eli Wilson
  • Publication number: 20230403459
    Abstract: A system is provided which obtains images of a physical object captured by an AR recording device in a 3D scene. The system measures a level of diversity of the obtained images, for a respective image, based on at least: a distance and angle; a lighting condition; and a percentage of occlusion. The system generates, based on the level of diversity, a first visualization of additional images to be captured by projecting, on a display of the recording device, first instructions for capturing the additional images using the AR recording device. The system trains a model based on the collected data. The system performs an error analysis on the collected data to estimate an error rate for each image of the collected data. The system generates, based on the error analysis, a second visualization of further images to be captured. The model is further trained based on the collected data.
    Type: Application
    Filed: June 14, 2022
    Publication date: December 14, 2023
    Applicant: Palo Alto Research Center Incorporated
    Inventors: Matthew A. Shreve, Robert R. Price
  • Patent number: 11816809
    Abstract: Embodiments described herein provide a system for facilitating dynamic assistance to a user in an augmented reality (AR) environment of an AR device. During operation, the system detects a first element of an object using an object detector, wherein the object is associated with a task and the first element is associated with a step of the task. The system then determines an orientation and an alignment of the first element in the physical world of the user, and an overlay for the first element. The overlay can distinctly highlight one or more regions of the first element and indicate how the first element fits in the object. The system then applies the overlay to the one or more regions of the first element at the determined orientation in the AR environment.
    Type: Grant
    Filed: May 18, 2022
    Date of Patent: November 14, 2023
    Assignee: Xerox Corporation
    Inventors: Hsuan-Ting Wu, Robert R. Price
  • Publication number: 20230350880
    Abstract: A method of labeling a dataset includes inputting a testing set comprising a plurality of input data samples into a plurality of pre-trained machine learning models to generate a set of embeddings output by the plurality of pre-trained machine learning models. The method further includes performing an iterative cluster labeling algorithm that includes generating a plurality of clusterings from the set of embeddings, analyzing the plurality of clusterings to identify a target embedding with a highest duster quality, analyzing the target embedding to determine a compactness for each of the plurality of clusterings of the target embedding, and identifying a target cluster among the plurality of clusterings of the target embedding based on the compactness. The method further includes assigning pseudo-labels to the subset of the plurality of input data samples that are members of the target duster.
    Type: Application
    Filed: July 7, 2023
    Publication date: November 2, 2023
    Inventors: Matthew Shreve, Francisco E. Torres, Raja Bala, Robert R. Price, Pei Li
  • Patent number: 11714802
    Abstract: A method of labeling a dataset of input samples for a machine learning task includes selecting a plurality of pre-trained machine learning models that are related to a machine learning task. The method further includes processing a plurality of input data samples through each of the pre-trained models to generate a set of embeddings. The method further includes generating a plurality of clusterings from the set of embeddings. The method further includes analyzing, by a processing device, the plurality of clusterings to extract superclusters. The method further includes assigning pseudo-labels to the input samples based on analysis.
    Type: Grant
    Filed: April 2, 2021
    Date of Patent: August 1, 2023
    Assignee: Palo Alto Research Center Incorporated
    Inventors: Matthew Shreve, Francisco E. Torres, Raja Bala, Robert R. Price, Pei Li
  • Publication number: 20230108199
    Abstract: A system and method for forward path planning of cab trailer systems is provided. Movement of a robot moving forward is tracked and a trajectory of at least one trailer attached to a back of the robot is estimated separate from a path of the robot. The trajectory of the trailer is based on the movement of the robot. A test for collision of one of the trailers is performed by identifying an obstacle and determining a distance of each trailer from the obstacle based on estimated trajectory. The trajectory of the robot is moved away from the obstacle when the distance fails to satisfy a threshold distance from the obstacle.
    Type: Application
    Filed: October 4, 2021
    Publication date: April 6, 2023
    Inventors: Robert R. Price, Kent Evans
  • Patent number: 11580634
    Abstract: Embodiments described herein provide a system for assessing the surface of an object for detecting contamination or other defects. During operation, the system obtains an input image indicating the contamination on the object and generates a synthetic image using an artificial intelligence (AI) model based on the input image. The synthetic image can indicate the object without the contamination. The system then determines a difference between the input image and the synthetic image to identify an image area corresponding to the contamination. Subsequently, the system generates a contamination map of the contamination by highlighting the image area based on one or more image enhancement operations.
    Type: Grant
    Filed: November 12, 2021
    Date of Patent: February 14, 2023
    Assignee: Palo Alto Research Center Incorporated
    Inventor: Robert R. Price
  • Patent number: 11580450
    Abstract: Embodiments described herein provide a system for facilitating efficient dataset management. During operation, the system obtains a first dataset comprising a plurality of elements. The system then determines a set of categories for a respective element of the plurality of elements by applying a plurality of AI models to the first dataset. A respective category can correspond to an AI model. Subsequently, the system selects a set of sample elements associated with a respective category of a respective AI model and determines a second dataset based on the selected sample elements.
    Type: Grant
    Filed: January 16, 2020
    Date of Patent: February 14, 2023
    Assignee: Palo Alto Research Center Incorporated
    Inventors: Robert R. Price, Matthew A. Shreve