Patents by Inventor Jay Yagnik

Jay Yagnik 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: 10115146
    Abstract: Implementations include systems and methods for scoring candidates for set recommendation problems. An example method includes repeating, for each code in code arrays for items in a set of items, determining a most common value for the code. In some implementations, the method includes determining that the most common value occurs with a frequency that meets an occurrence threshold and adding the code and the most common value to set-inclusion criteria. In other implementations, the method includes determining a value for the code from a code array for a seed item and adding the code and the most common value to set-inclusion criteria when the value for the code from the code array for the seed item matches the most common value. The method may also include evaluating a similarity with a candidate item based on the set-inclusion criteria and basing a recommendation regarding the candidate item on the similarity.
    Type: Grant
    Filed: April 16, 2015
    Date of Patent: October 30, 2018
    Assignee: GOOGLE LLC
    Inventors: John Roberts Anderson, Ryan Michael Rifkin, Jay Yagnik, Rasmus Larsen, Sarvjeet Singh, Yi-Fan Chen, Anandsudhakar Kesari
  • Patent number: 10061999
    Abstract: An example method is disclosed that includes identifying a training set of images, wherein each image in the training set has an identified bounding box that comprises an object class and an object location for an object in the image. The method also includes segmenting each image of the training set, wherein segments comprise sets of pixels that share visual characteristics, and wherein each segment is associated with an object class. The method further includes clustering the segments that are associated with the same object class, and generating a data structure based on the clustering, wherein entries in the data structure comprise visual characteristics for prototypical segments of objects having the object class and further comprise one or more potential bounding boxes for the objects, wherein the data structure is usable to predict bounding boxes of additional images that include an object having the object class.
    Type: Grant
    Filed: October 31, 2016
    Date of Patent: August 28, 2018
    Assignee: GOOGLE LLC
    Inventors: Vivek Kwatra, Jay Yagnik, Alexander Toshkov Toshev
  • Patent number: 10049305
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classification using a neural network. One of the methods for processing an input through each of multiple layers of a neural network to generate an output, wherein each of the multiple layers of the neural network includes a respective multiple nodes includes for a particular layer of the multiple layers: receiving, by a classification system, an activation vector as input for the particular layer, selecting one or more nodes in the particular layer using the activation vector and a hash table that maps numeric values to nodes in the particular layer, and processing the activation vector using the selected nodes to generate an output for the particular layer.
    Type: Grant
    Filed: July 21, 2017
    Date of Patent: August 14, 2018
    Assignee: Google LLC
    Inventors: Sudheendra Vijayanarasimhan, Jay Yagnik
  • Patent number: 9971940
    Abstract: Provided content is determined to contain an asset represented by reference content by comparing digital fingerprints of the provided content and the reference content. The fingerprints of the reference content and the provided content are generated using a convolutional neural network (CNN). The CNN is trained using a plurality of frame triplets including an anchor frame representing the reference content, a positive frame which is a transformation of the anchor frame, and a negative frame representing content that is not the reference content. The provided content is determined to contain the asset represented by the reference content based on a similarity measure between the generated fingerprints. If the provided content is determined to contain the asset represented by the reference content, a policy associated with the asset is enforced on the provided content.
    Type: Grant
    Filed: August 8, 2016
    Date of Patent: May 15, 2018
    Assignee: GOOGLE LLC
    Inventors: Luciano Sbaiz, Jay Yagnik, King Hong Thomas Leung, Hanna Pasula, Thomas Chadwick Walters, Thomas Bugnon, Matthias Rochus Konrad
  • Patent number: 9870383
    Abstract: The disclosed embodiments describe a method, an apparatus, an application specific integrated circuit, and a server that provides a fast and efficient look up for data analysis. The apparatus and server may be configured to obtain data segments from a plurality of input devices. The data segments may be individual unique subsets of the entire data set obtained by a plurality input devices. A hash function may be applied to an aggregated set of the data segments. A result of the hash function may be stored in a data structure. A codebook may be generated from the hash function results.
    Type: Grant
    Filed: April 10, 2015
    Date of Patent: January 16, 2018
    Assignee: GOOGLE LLC
    Inventor: Jay Yagnik
  • Publication number: 20170323183
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classification using a neural network. One of the methods for processing an input through each of multiple layers of a neural network to generate an output, wherein each of the multiple layers of the neural network includes a respective multiple nodes includes for a particular layer of the multiple layers: receiving, by a classification system, an activation vector as input for the particular layer, selecting one or more nodes in the particular layer using the activation vector and a hash table that maps numeric values to nodes in the particular layer, and processing the activation vector using the selected nodes to generate an output for the particular layer.
    Type: Application
    Filed: July 21, 2017
    Publication date: November 9, 2017
    Inventors: Sudheendra Vijayanarasimhan, Jay Yagnik
  • Patent number: 9721190
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classification using a neural network. One of the methods for processing an input through each of multiple layers of a neural network to generate an output, wherein each of the multiple layers of the neural network includes a respective multiple nodes includes for a particular layer of the multiple layers: receiving, by a classification system, an activation vector as input for the particular layer, selecting one or more nodes in the particular layer using the activation vector and a hash table that maps numeric values to nodes in the particular layer, and processing the activation vector using the selected nodes to generate an output for the particular layer.
    Type: Grant
    Filed: November 5, 2015
    Date of Patent: August 1, 2017
    Assignee: Google Inc.
    Inventors: Sudheendra Vijayanarasimhan, Jay Yagnik
  • Patent number: 9684715
    Abstract: This disclosure relates to audio identification using ordinal transformations. A media matching component receives a sample audio file. The sample audio file can include, for example, a cover song. The media matching component includes a vector component that computes a set of vectors using auditory feature values included in the sample audio file. A hashing component employs a hash function to generate a fingerprint, including a set of sub-fingerprints, for the sample audio file using the set of vectors. The fingerprint is invariant to variations including but not limited to variations in key, instrumentation, encoding formats, performers, performance conditions, arrangement, and/or recording and processing variations. An identification component determines if any reference audio files are similar to the sample audio file using the fingerprint and/or sub-fingerprints, and identifies any similar reference audio files.
    Type: Grant
    Filed: March 8, 2012
    Date of Patent: June 20, 2017
    Assignee: Google Inc.
    Inventors: David Ross, Jay Yagnik
  • Patent number: 9619521
    Abstract: A segmentation annotation technique for media items is disclosed herein. Given a weakly labeled media item, spatiotemporal masks may be generated for each of the concepts with which it is labeled. Segments may be ranked by the likelihood that they correspond to a given concept. The ranked concept segments may be utilized to train a classifier that, in turn, may be used to classify untagged or new media items.
    Type: Grant
    Filed: December 30, 2013
    Date of Patent: April 11, 2017
    Assignee: Google Inc.
    Inventors: Rahul Sukthankar, Jay Yagnik
  • Patent number: 9569847
    Abstract: One of the described methods includes receiving a plurality of images from a camera, the plurality of images comprising a sequence; identifying one or more two-dimensional features in each of a plurality of images in the received sequence of images; associating a three-dimensional point with each of the identified one or more two-dimensional features; tracking each of the one or more two-dimensional features through successive images in the plurality of images; and iteratively minimizing a two-dimensional image error between the tracked each of the one or more two-dimensional features and an image reprojection with respect to the three-dimensional point corresponding to the one or more two-dimensional features and a three-dimensional position of the camera corresponding to one or more of the plurality of images.
    Type: Grant
    Filed: February 13, 2015
    Date of Patent: February 14, 2017
    Assignee: Google Inc.
    Inventors: Dennis Strelow, Jay Yagnik
  • Patent number: 9552511
    Abstract: A method includes identifying a named entity, retrieving images associated with the named entity, and using a face detection algorithm to perform face detection on the retrieved images to detect faces in the retrieved images. At least one representative face image from the retrieved images is identified, and the representative face image is used to identify one or more additional images representing the at least one named entity.
    Type: Grant
    Filed: May 21, 2015
    Date of Patent: January 24, 2017
    Assignee: Google Inc.
    Inventor: Jay Yagnik
  • Patent number: 9524487
    Abstract: A system and methods for automatically detecting temporal music trends by observing music consumption by users of online services, for example, social networks, and user sharing habits. In some embodiments, the system and methods gather music consumption patterns (e.g., downloading, listening, sharing or the like) of users, including music identifiers for a track, album, or playlist in a user's music library and time stamps that indicate consumption times corresponding to the music identifiers. A temporal trends detection engine determines music of interest to users by analyzing music consumption patterns of users, user interests and tastes in music, and social affinity between users. A recommendations engine automatically generates and transmits recommendations of music determined by the temporal trends detection engine to be of interest to users.
    Type: Grant
    Filed: May 8, 2012
    Date of Patent: December 20, 2016
    Assignee: Google Inc.
    Inventors: Jay Yagnik, Douglas Eck
  • Patent number: 9508023
    Abstract: This disclosure relates to transformation invariant media matching. A fingerprinting component can generate a transformation invariant identifier for media content by adaptively encoding the relative ordering of interest points in media content. The interest points can be grouped into subsets, and stretch invariant descriptors can be generated for the subsets based on ratios of coordinates of interest points included in the subsets. The stretch invariant descriptors can be aggregated into a transformation invariant identifier. An identification component compares the identifier against a set of identifiers for known media content, and the media content can be matched or identified as a function of the comparison.
    Type: Grant
    Filed: April 21, 2014
    Date of Patent: November 29, 2016
    Assignee: Google Inc.
    Inventors: Matthew Sharifi, Sergey Ioffe, Jay Yagnik, Gheorghe Postelnicu, Dominik Roblek, George Tzanetakis
  • Patent number: 9483701
    Abstract: A computing device segments an image into a plurality of segments, wherein each segment of the plurality of segments has a segment location and a set of pixels that share visual characteristics. The computing device determines an initial set of bounding boxes for the image based on the plurality of segments. The computing device determines a reduced set of bounding boxes based on combining bounding boxes of the initial set of bounding boxes, the reduced set of bounding boxes corresponding to one or more objects in the image, each of the one or more objects having an object class and an object location.
    Type: Grant
    Filed: November 17, 2011
    Date of Patent: November 1, 2016
    Assignee: GOOGLE INC.
    Inventors: Vivek Kwatra, Jay Yagnik, Alexander T. Toshev
  • Patent number: 9445047
    Abstract: A method and system include identifying, by a processing device, at least one media clip captured by at least one camera for an event, detecting at least one human object in the at least one media clip, and calculating, by the processing device, a region in the at least one media clip containing a focus of attention of the detected human object.
    Type: Grant
    Filed: March 20, 2014
    Date of Patent: September 13, 2016
    Assignee: Google Inc.
    Inventors: Christian Frueh, Krishna Bharat, Jay Yagnik
  • Publication number: 20160224826
    Abstract: A method includes identifying a named entity, retrieving images associated with the named entity, and using a face detection algorithm to perform face detection on the retrieved images to detect faces in the retrieved images. At least one representative face image from the retrieved images is identified, and the representative face image is used to identify one or more additional images representing the at least one named entity.
    Type: Application
    Filed: May 21, 2015
    Publication date: August 4, 2016
    Inventor: Jay Yagnik
  • Publication number: 20160180200
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classification using a neural network. One of the methods for processing an input through each of multiple layers of a neural network to generate an output, wherein each of the multiple layers of the neural network includes a respective multiple nodes includes for a particular layer of the multiple layers: receiving, by a classification system, an activation vector as input for the particular layer, selecting one or more nodes in the particular layer using the activation vector and a hash table that maps numeric values to nodes in the particular layer, and processing the activation vector using the selected nodes to generate an output for the particular layer.
    Type: Application
    Filed: November 5, 2015
    Publication date: June 23, 2016
    Inventors: Sudheendra Vijayanarasimhan, Jay Yagnik
  • Patent number: 9373040
    Abstract: A motion manifold system analyzes a set of videos, identifying image patches within those videos corresponding to regions of interest and identifying patch trajectories by tracking the movement of the regions over time in the videos. Based on the patch identification and tracking, the system produces a motion manifold data structure that captures the way in which the same semantic region can have different visual representations over time. The motion manifold can then be applied to determine the semantic similarity between different patches, or between higher-level constructs such as images or video segments, including detecting semantic similarity between patches or other constructs that are visually dissimilar.
    Type: Grant
    Filed: January 9, 2012
    Date of Patent: June 21, 2016
    Assignee: Google Inc.
    Inventors: Rahul Sukthankar, Jay Yagnik
  • Patent number: 9367612
    Abstract: A system identifies a set of initial segments of a time-based data item, such as audio. The segments can be defined at regular time intervals within the time-based data item. The initial segments are short segments. The system computes a short-timescale vectorial representation for each initial segment and compares the short-timescale vectorial representation for each initial segment with other short-timescale vectorial representations of the segments in a time duration within the time-based data item (e.g., audio) immediately preceding or immediately following the initial segment. The system generates a representation of long-timescale information for the time-based data item based on a comparison of the short-timescale vectorial representations of the initial segments and the short-timescale vectorial representations of immediate segments. The representation of long-timescale information identifies an underlying repetition structure of the time-based data item, such as rhythm or phrasing in an audio item.
    Type: Grant
    Filed: November 18, 2011
    Date of Patent: June 14, 2016
    Assignee: GOOGLE INC.
    Inventors: Douglas Eck, Jay Yagnik
  • Publication number: 20160014440
    Abstract: A video demographics analysis system selects a training set of videos to use to correlate viewer demographics and video content data. The video demographics analysis system extracts demographic data from viewer profiles related to videos in the training set and creates a set of demographic distributions, and also extracts video data from videos in the training set. The video demographics analysis system correlates the viewer demographics with the video data of videos viewed by that viewer. Using the prediction model produced by the machine learning process, a new video about which there is no a priori knowledge can be associated with a predicted demographic distribution specifying probabilities of the video appealing to different types of people within a given demographic category, such as people of different ages within an age demographic category.
    Type: Application
    Filed: October 1, 2012
    Publication date: January 14, 2016
    Inventors: CORINNA CORTES, SANJIV KUMAR, Ameesh Makadia, Gideon Mann, Jay Yagnik, Ming Zhao