Patents by Inventor Victor Sevillano Plaza

Victor Sevillano Plaza 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).

  • Patent number: 11468683
    Abstract: A method for determining population density of a defined space from multi-camera sourced imagery includes loading a set of images acquired from multiple different cameras positioned about the defined space, locating different individuals within each of the images and computing a population distribution of the located different individuals in respect to different locations of the defined space. The method additionally includes submitting each of the images to a convolutional neural network as training data, each in association with a correspondingly computed population distribution. Subsequent to the submission, contemporaneous imagery from the different cameras is acquired in real time and submitted to the neural network, in response to which, a predicted population distribution for the defined space is received from the neural network. Finally, a message is displayed that includes information correlating at least a portion of the population distribution with a specific location of the defined space.
    Type: Grant
    Filed: February 1, 2021
    Date of Patent: October 11, 2022
    Assignee: Royal Caribbean Cruises Ltd.
    Inventors: Yunus Genes, Victor Sevillano Plaza
  • Publication number: 20210182571
    Abstract: A method for determining population density of a defined space from multi-camera sourced imagery includes loading a set of images acquired from multiple different cameras positioned about the defined space, locating different individuals within each of the images and computing a population distribution of the located different individuals in respect to different locations of the defined space. The method additionally includes submitting each of the images to a convolutional neural network as training data, each in association with a correspondingly computed population distribution. Subsequent to the submission, contemporaneous imagery from the different cameras is acquired in real time and submitted to the neural network, in response to which, a predicted population distribution for the defined space is received from the neural network. Finally, a message is displayed that includes information correlating at least a portion of the population distribution with a specific location of the defined space.
    Type: Application
    Filed: February 1, 2021
    Publication date: June 17, 2021
    Inventors: Yunus Genes, Victor Sevillano Plaza
  • Patent number: 10909388
    Abstract: A method for determining population density of a defined space from multi-camera sourced imagery includes loading a set of images acquired from multiple different cameras positioned about the defined space, locating different individuals within each of the images and computing a population distribution of the located different individuals in respect to different locations of the defined space. The method additionally includes submitting each of the images to a convolutional neural network as training data, each in association with a correspondingly computed population distribution. Subsequent to the submission, contemporaneous imagery from the different cameras is acquired in real time and submitted to the neural network, in response to which, a predicted population distribution for the defined space is received from the neural network. Finally, a message is displayed that includes information correlating at least a portion of the population distribution with a specific location of the defined space.
    Type: Grant
    Filed: May 3, 2019
    Date of Patent: February 2, 2021
    Assignee: ROYAL CARIBBEAN CRUISES LTD.
    Inventors: Yunus Genes, Victor Sevillano Plaza
  • Publication number: 20200349360
    Abstract: A method for determining population density of a defined space from multi-camera sourced imagery includes loading a set of images acquired from multiple different cameras positioned about the defined space, locating different individuals within each of the images and computing a population distribution of the located different individuals in respect to different locations of the defined space. The method additionally includes submitting each of the images to a convolutional neural network as training data, each in association with a correspondingly computed population distribution. Subsequent to the submission, contemporaneous imagery from the different cameras is acquired in real time and submitted to the neural network, in response to which, a predicted population distribution for the defined space is received from the neural network. Finally, a message is displayed that includes information correlating at least a portion of the population distribution with a specific location of the defined space.
    Type: Application
    Filed: May 3, 2019
    Publication date: November 5, 2020
    Inventors: Yunus Genes, Victor Sevillano Plaza