Patents by Inventor Leonid Sigal

Leonid Sigal 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: 20190236136
    Abstract: A dialog engine configured to answer a sequence of questions related to an image. An attention module residing in the dialog engine includes an attention retrieval process and a tentative attention process. The attention retrieval process retrieves a relevant attention map that may have previously been used to answer a previous query. The tentative attention process generates a tentative attention map based on an image and other input parameters. The attention module combines the relevant attention map and the tentative attention map to generate a fused attention map. Based on the fused attention map, the dialog engine generates a response to the query. Finally, the dialog engine stores the fused attention map in an attention memory for use in answering future queries.
    Type: Application
    Filed: January 30, 2018
    Publication date: August 1, 2019
    Inventors: Leonid SIGAL, Andreas LEHRMANN, Paul Hongsuck SEO
  • Patent number: 10339706
    Abstract: A system and method of estimating the body shape of an individual from input data such as images or range maps. The body may appear in one or more poses captured at different times and a consistent body shape is computed for all poses. The body may appear in minimal tight-fitting clothing or in normal clothing wherein the described method produces an estimate of the body shape under the clothing. Clothed or bare regions of the body are detected via image classification and the fitting method is adapted to treat each region differently. Body shapes are represented parametrically and are matched to other bodies based on shape similarity and other features. Standard measurements are extracted using parametric or non-parametric functions of body shape. The system components support many applications in body scanning, advertising, social networking, collaborative filtering and Internet clothing shopping.
    Type: Grant
    Filed: June 14, 2018
    Date of Patent: July 2, 2019
    Assignee: BROWN UNIVERSITY
    Inventors: Michael J. Black, Alexandru O. Balan, Alexander W. Weiss, Leonid Sigal, Matthew M. Loper, Timothy S. St. Clair
  • Patent number: 10331676
    Abstract: Items of interest within digital information may be detected and associated with a label that provides context to the item of interest. The label may describe an item category of the item of interest. The knowledge base of item categories may be limited. Additional item categories may be learned by accessing sets of vocabulary that may relate to the known item categories.
    Type: Grant
    Filed: April 13, 2016
    Date of Patent: June 25, 2019
    Assignee: Disney Enterprises, Inc.
    Inventors: Yanwei Fu, Leonid Sigal
  • Publication number: 20190138850
    Abstract: Systems, methods and articles of manufacture for training a convolutional neural network for feature recognition within digital images. A spatial context neural network is trained using a plurality of patches cropped from a plurality of digital images, the spatial context neural network comprising a first convolutional neural network configured to predict a feature representation for a first specified portion of a first digital image, a second convolutional neural network configured to compute a feature representation for a second specified portion of a second digital image, and a spatial context module that accepts output of the first and second convolutional neural networks as input. The second convolutional neural network is refined by regressing features of the second convolutional neural network to features of the first convolutional neural network. The refined second convolutional neural network is used to recognize one or more features within a third digital image.
    Type: Application
    Filed: November 9, 2017
    Publication date: May 9, 2019
    Inventors: Leonid SIGAL, Zuxuan WU
  • Patent number: 10223580
    Abstract: Methods and systems for video action recognition using poselet keyframes are disclosed. An action recognition model may be implemented to spatially and temporally model discriminative action components as a set of discriminative keyframes. One method of action recognition may include the operations of selecting a plurality of poselets that are components of an action, encoding each of a plurality of video frames as a summary of the detection confidence of each of the plurality of poselets for the video frame, and encoding correlations between poselets in the encoded video frames.
    Type: Grant
    Filed: September 12, 2013
    Date of Patent: March 5, 2019
    Assignee: Disney Enterprises, Inc.
    Inventors: Michail Raptis, Leonid Sigal
  • Patent number: 10163036
    Abstract: One or more image parameters of an image may be analyzed using a hierarchical set of models. Executing individual models in the set of models may generate outputs from analysis of different image parameters of the image. Inputs of one or more of the models may be conditioned on a set of outputs derived from one or more preceding model in the hierarchy.
    Type: Grant
    Filed: September 22, 2016
    Date of Patent: December 25, 2018
    Assignee: Disney Enterprises, Inc.
    Inventors: Andreas Lehrmann, Leonid Sigal
  • Patent number: 10163020
    Abstract: There is provided a system configured to receive a plurality of images, analyze a set of features of the plurality of images to determine a difference between a first training performance of a plurality of independent detectors based on one or more of individual attributes and a second training performance of a plurality of joint detectors based on one or more of composite attributes, select, based on the analyzing, either one of the plurality of independent detectors or one of the plurality of joint detectors for identifying a plurality of objects in the plurality of images, and identify the plurality of objects in the plurality of images, using the selected one of the plurality of independent detectors utilizing the one or more of the individual attributes or using the selected one of the plurality of joint detectors utilizing the one or more of the composite attributes.
    Type: Grant
    Filed: June 4, 2018
    Date of Patent: December 25, 2018
    Assignee: Disney Enterprises, Inc.
    Inventors: Leonid Sigal, Arik Shamir, Guy Rosenthal
  • Publication number: 20180293788
    Abstract: A system and method of estimating the body shape of an individual from input data such as images or range maps. The body may appear in one or more poses captured at different times and a consistent body shape is computed for all poses. The body may appear in minimal tight-fitting clothing or in normal clothing wherein the described method produces an estimate of the body shape under the clothing. Clothed or bare regions of the body are detected via image classification and the fitting method is adapted to treat each region differently. Body shapes are represented parametrically and are matched to other bodies based on shape similarity and other features. Standard measurements are extracted using parametric or non-parametric functions of body shape. The system components support many applications in body scanning, advertising, social networking, collaborative filtering and Internet clothing shopping.
    Type: Application
    Filed: June 14, 2018
    Publication date: October 11, 2018
    Inventors: Michael J. BLACK, Alexandru O. BALAN, Alexander W. Weiss, Leonid SIGAL, Matthew M. LOPER, Timothy S. ST. CLAIR
  • Publication number: 20180285670
    Abstract: There is provided a system comprising a memory and a processor configured to receive a plurality of images, train a plurality of independent detectors for identifying a first plurality of objects in the plurality of images based on individual attributes including a first attribute and a second attribute, train a plurality of joint detectors for identifying the first plurality of objects in the plurality of images based on composite attributes including a plurality of composite attributes each including the first attribute and the second attribute, analyze features of the plurality of images to determine a difference between a first training performance of the independent detectors and a second training performance of the joint detectors, and select, based on the analyzing, between using the independent detectors and using the joint detectors for identifying a second plurality of objects in the plurality of images using a first new attribute and a second new attribute in the attribute database.
    Type: Application
    Filed: June 4, 2018
    Publication date: October 4, 2018
    Inventors: Leonid Sigal, Arik Shamir, Guy Rosenthal
  • Publication number: 20180276286
    Abstract: There is provided a system including a computing platform having a hardware processor and a memory, and a metadata extraction and management unit stored in the memory. The hardware processor is configured to execute the metadata extraction and management unit to extract a plurality of metadata types from a media asset sequentially and in accordance with a prioritized order of extraction based on metadata type, aggregate the plurality of metadata types to produce an aggregated metadata describing the media asset, use the aggregated metadata to include at least one database entry in a graphical database, wherein the at least one database entry describes the media asset, display a user interface for a user to view tags of metadata associated with the media asset, and correcting presence of one of the tags of metadata associated with the media asset, in response to an input from the user via the user interface.
    Type: Application
    Filed: May 21, 2018
    Publication date: September 27, 2018
    Inventors: Miquel Angel Farre Guiu, Marc Junyent Martin, Jordi Pont-Tuset, Pablo Beltran Sanchidrian, Nimesh Narayan, Leonid Sigal, Aljoscha Smolic, Anthony M. Accardo
  • Patent number: 10073861
    Abstract: Systems, methods, and computer program products to perform an operation comprising assigning each of a plurality of nodes of a graph to a distinct image, of a plurality of images, wherein the graph represents a story, wherein each node corresponds to a respective element of the story, wherein each node comprises: (i) an attribute and (ii) a text of the respective element of the story, wherein the plurality of graph nodes are assigned based on a set of attributes of each of the plurality of images and the attribute of each node, and generating a visual depiction of the story, wherein the visual depiction comprises an ordered representation of each of the distinct images and the text of each respective element of the story.
    Type: Grant
    Filed: September 3, 2015
    Date of Patent: September 11, 2018
    Assignee: Disney Enterprises, Inc.
    Inventors: Ariel Shamir, Oz Radiano, Leonid Sigal, Moshe B. Mahler
  • Patent number: 10061986
    Abstract: There is provided a system comprising a memory and a processor configured to receive a media content depicting an activity, extract a first plurality of features from a first segment of the media content, make a first prediction that the media content depicts a first activity based on the first plurality of features, wherein the first prediction has a first confidence level, extract a second plurality of features from a second segment of the media content, the second segment temporally following the first segment in the media content, make a second prediction that the media content depicts the first activity based on the second plurality of features, wherein the second prediction has a second confidence level, determine that the media content depicts the first activity based on the first prediction and the second prediction, wherein the second confidence level is at least as high as the first confidence level.
    Type: Grant
    Filed: July 14, 2016
    Date of Patent: August 28, 2018
    Assignee: Disney Enterprises, Inc.
    Inventors: Leonid Sigal, Shugao Ma
  • Publication number: 20180189569
    Abstract: There is provided a system including a non-transitory memory storing an executable code and a hardware processor executing the executable code to receive a plurality of training contents depicting a plurality of activities, extract training object data from the plurality of training contents including a first training object data corresponding to a first activity, extract training scene data from the plurality of training contents including a first training scene data corresponding to the first activity, determine that a probability of the first activity is maximized when the first training object data and the first training scene data both exist in a sample media content.
    Type: Application
    Filed: February 28, 2018
    Publication date: July 5, 2018
    Inventors: Zuxuan Wu, Yanwei Fu, Leonid Sigal
  • Patent number: 10013621
    Abstract: There is provided a system including a memory and a processor to receive images. The processor is further to train independent detectors for identifying first objects in the images based on individual attributes including a first attribute and a second attribute. The processor is also to train joint detectors for identifying first objects in the images based on composite attributes including a composite attributes each including the first attribute and the second attribute. The processor is to analyze features of the images to determine a difference between a first training performance of the independent detectors and a second training performance of the joint detectors. Lastly, the processor is to select, based on the analyzing, between using the independent detectors and using the joint detectors for identifying second objects in the images using a third attribute and a fourth attribute in the attribute database.
    Type: Grant
    Filed: October 4, 2016
    Date of Patent: July 3, 2018
    Assignee: Disney Enterprises, Inc.
    Inventors: Leonid Sigal, Arik Shamir, Guy Rosenthal
  • Patent number: 10007713
    Abstract: There are provided systems and methods for performing metadata extraction and management. Such a system includes a computing platform having a hardware processor, a system memory, and metadata extraction and management unit stored in the system memory. The system is configured to extract multiple metadata types from a media asset, and to aggregate the multiple metadata types to produce an aggregated metadata describing the media asset. The system is further configured to transform the aggregated metadata into at least one database entry identifying the media asset, and to map the at least one database entry into a graphical database so as to relate the media asset to at least one other media asset represented in the graphical database.
    Type: Grant
    Filed: October 15, 2015
    Date of Patent: June 26, 2018
    Assignee: Disney Enterprises, Inc.
    Inventors: Miguel Angel Farre Guiu, Marc Junyent Martin, Jordi Pont-Tuset, Pablo Beltran, Nimesh Narayan, Leonid Sigal, Aljoscha Smolic, Anthony M. Accardo
  • Patent number: 10002460
    Abstract: A system and method of estimating the body shape of an individual from input data such as images or range maps. The body may appear in one or more poses captured at different times and a consistent body shape is computed for all poses. The body may appear in minimal tight-fitting clothing or in normal clothing wherein the described method produces an estimate of the body shape under the clothing. Clothed or bare regions of the body are detected via image classification and the fitting method is adapted to treat each region differently. Body shapes are represented parametrically and are matched to other bodies based on shape similarity and other features. Standard measurements are extracted using parametric or non-parametric functions of body shape. The system components support many applications in body scanning, advertising, social networking, collaborative filtering and Internet clothing shopping.
    Type: Grant
    Filed: October 16, 2015
    Date of Patent: June 19, 2018
    Assignee: BROWN UNIVERSITY
    Inventors: Michael J. Black, Alexandru O. Balan, Alexander W. Weiss, Leonid Sigal, Matthew M. Loper, Timothy S. St. Clair
  • Patent number: 9940522
    Abstract: There is provided a system including a non-transitory memory storing an executable code and a hardware processor executing the executable code to receive a plurality of training contents depicting a plurality of activities, extract training object data from the plurality of training contents including a first training object data corresponding to a first activity, extract training scene data from the plurality of training contents including a first training scene data corresponding to the first activity, determine that a probability of the first activity is maximized when the first training object data and the first training scene data both exist in a sample media content.
    Type: Grant
    Filed: July 15, 2016
    Date of Patent: April 10, 2018
    Assignee: Disney Enterprises, Inc.
    Inventors: Zuxuan Wu, Yanwei Fu, Leonid Sigal
  • Publication number: 20180096259
    Abstract: Training data from multiple types of sensors and captured in previous capture sessions can be fused within a physics-based tracking framework to train motion priors using different deep learning techniques, such as convolutional neural networks (CNN) and Recurrent Temporal Restricted Boltzmann Machines (RTRBMs). In embodiments employing one or more CNNs, two streams of filters can be used. In those embodiments, one stream of the filters can be used to learn the temporal information and the other stream of the filters can be used to learn spatial information. In embodiments employing one or more RTRBMs, all visible nodes of the RTRBMs can be clamped with values obtained from the training data or data synthesized from the training data. In cases where sensor data is unavailable, the input nodes may be unclamped and the one or more RTRBMs can generate the missing sensor data.
    Type: Application
    Filed: September 30, 2016
    Publication date: April 5, 2018
    Applicant: Disney Enterprises, Inc.
    Inventors: Sheldon Andrews, Ivan Huerta Casado, Kenneth J. Mitchell, Leonid Sigal
  • Publication number: 20180096192
    Abstract: There is provided a system comprising a memory and a processor configured to receive a plurality of images, train a plurality of independent detectors for identifying a first plurality of objects in the plurality of images based on individual attributes including a first attribute and a second attribute, train a plurality of joint detectors for identifying the first plurality of objects in the plurality of images based on composite attributes including a plurality of composite attributes each including the first attribute and the second attribute, analyze features of the plurality of images to determine a difference between a first training performance of the independent detectors and a second training performance of the joint detectors, and select, based on the analyzing, between using the independent detectors and using the joint detectors for identifying a second plurality of objects in the plurality of images using a first new attribute and a second new attribute in the attribute database.
    Type: Application
    Filed: October 4, 2016
    Publication date: April 5, 2018
    Inventors: Leonid Sigal, Arik Shamir, Guy Rosenthal
  • Publication number: 20180089580
    Abstract: Techniques are disclosed for identifying and filtering outliers from a sample set of data prior to training a classifier on an object using the sample set. A data set including a plurality of samples used to train a classification model is retrieved. The samples in the data set have a feature dimensionality. A graph of the data set is built. Each node in the graph corresponds to a sample in the data set and edges connecting the nodes correspond to a measure of similarity between the nodes. The feature dimensionality of the sample data set is reduced based on a topology of the graph. One or more outliers in the data set are identified based on the reduced feature dimensionality.
    Type: Application
    Filed: September 27, 2016
    Publication date: March 29, 2018
    Inventors: Yanwei FU, Leonid SIGAL