Search Patents
  • Publication number: 20160328613
    Abstract: Methods and systems for online domain adaptation for multi-object tracking. Video of an area of interest can be captured with an image-capturing unit. The video (e.g., video images) can be analyzed with a pre-trained object detector utilizing online domain adaptation including convex multi-task learning and an associated self-tuning stochastic optimization procedure to jointly adapt online all trackers associated with the pre-trained object detector and a pre-trained category-level model from the trackers in order to efficiently track a plurality of objects in the video captured by the image-capturing unit.
    Type: Application
    Filed: May 5, 2015
    Publication date: November 10, 2016
    Inventors: Adrien Gaidon, Eleonora Vig
  • Publication number: 20170308770
    Abstract: A method for generating a system for predicting saliency in an image and method of use of the prediction system are described. Attention maps for each of a set of training images are used to train the system. The training includes passing the training images though a neural network and optimizing an objective function over the training set which is based on a distance measure computed between a first probability distribution computed for a saliency map output by the neural network and a second probability distribution computed for the attention map for the respective training image. The trained neural network is suited to generation of saliency maps for new images.
    Type: Application
    Filed: April 26, 2016
    Publication date: October 26, 2017
    Applicant: Xerox Corporation
    Inventors: Saumya Jetley, Naila Murray, Eleonora Vig
  • Patent number: 9830529
    Abstract: A method for generating a system for predicting saliency in an image and method of use of the prediction system are described. Attention maps for each of a set of training images are used to train the system. The training includes passing the training images though a neural network and optimizing an objective function over the training set which is based on a distance measure computed between a first probability distribution computed for a saliency map output by the neural network and a second probability distribution computed for the attention map for the respective training image. The trained neural network is suited to generation of saliency maps for new images.
    Type: Grant
    Filed: April 26, 2016
    Date of Patent: November 28, 2017
    Assignee: XEROX CORPORATION
    Inventors: Saumya Jetley, Naila Murray, Eleonora Vig
  • Patent number: 9984315
    Abstract: Methods and systems for online domain adaptation for multi-object tracking. Video of an area of interest can be captured with an image-capturing unit. The video (e.g., video images) can be analyzed with a pre-trained object detector utilizing online domain adaptation including convex multi-task learning and an associated self-tuning stochastic optimization procedure to jointly adapt online all trackers associated with the pre-trained object detector and a pre-trained category-level model from the trackers in order to efficiently track a plurality of objects in the video captured by the image-capturing unit.
    Type: Grant
    Filed: May 5, 2015
    Date of Patent: May 29, 2018
    Assignee: Condurent Business Services, LLC
    Inventors: Adrien Gaidon, Eleonora Vig
  • Publication number: 20180053057
    Abstract: A computer-implemented video classification method and system are disclosed. The method includes receiving an input video including a sequence of frames. At least one transformation of the input video is generated, each transformation including a sequence of frames. For the input video and each transformation, local descriptors are extracted from the respective sequence of frames. The local descriptors of the input video and each transformation are aggregated to form an aggregated feature vector with a first set of processing layers learned using unsupervised learning. An output classification value is generated for the input video, based on the aggregated feature vector with a second set of processing layers learned using supervised learning.
    Type: Application
    Filed: August 18, 2016
    Publication date: February 22, 2018
    Applicant: Xerox Corporation
    Inventors: César Roberto De Souza, Adrien Gaidon, Eleonora Vig, Antonio M. Lopez
  • Publication number: 20170243083
    Abstract: A system and method are suited for assessing video performance analysis. A computer graphics engine clones real-world data in a virtual world by decomposing the real-world data into visual components and objects in one or more object categories and populates the virtual world with virtual visual components and virtual objects. A scripting component controls the virtual visual components and the virtual objects in the virtual world based on the set of real-world data. A synthetic clone of the video sequence is generated based on the script controlling the virtual visual components and the virtual objects. The real-world data is compared with the synthetic clone of the video sequence and a transferability of conclusions from the virtual world to the real-world is assessed based on this comparison.
    Type: Application
    Filed: February 23, 2016
    Publication date: August 24, 2017
    Applicant: Xerox Corporation
    Inventors: Qiao Wang, Adrien Gaidon, Eleonora Vig
  • Patent number: 9946933
    Abstract: A computer-implemented video classification method and system are disclosed. The method includes receiving an input video including a sequence of frames. At least one transformation of the input video is generated, each transformation including a sequence of frames. For the input video and each transformation, local descriptors are extracted from the respective sequence of frames. The local descriptors of the input video and each transformation are aggregated to form an aggregated feature vector with a first set of processing layers learned using unsupervised learning. An output classification value is generated for the input video, based on the aggregated feature vector with a second set of processing layers learned using supervised learning.
    Type: Grant
    Filed: August 18, 2016
    Date of Patent: April 17, 2018
    Assignee: XEROX CORPORATION
    Inventors: César Roberto De Souza, Adrien Gaidon, Eleonora Vig, Antonio M. Lopez
  • Patent number: 10019652
    Abstract: A system and method are suited for assessing video performance analysis. A computer graphics engine clones real-world data in a virtual world by decomposing the real-world data into visual components and objects in one or more object categories and populates the virtual world with virtual visual components and virtual objects. A scripting component controls the virtual visual components and the virtual objects in the virtual world based on the set of real-world data. A synthetic clone of the video sequence is generated based on the script controlling the virtual visual components and the virtual objects. The real-world data is compared with the synthetic clone of the video sequence and a transferability of conclusions from the virtual world to the real-world is assessed based on this comparison.
    Type: Grant
    Filed: February 23, 2016
    Date of Patent: July 10, 2018
    Assignee: Xerox Corporation
    Inventors: Qiao Wang, Adrien Gaidon, Eleonora Vig
  • Publication number: 20160314351
    Abstract: A graphical user interface (GUI) of a business process management (BPM) system is provided to construct a process model that is displayed on a graphical display device as a graphical representation comprising nodes representing process events, activities, or decision points and including computer vision (CV) nodes representing video stream processing, with flow connectors defining operational sequences of nodes and data flow between nodes of the process model. The process model is executed to perform a process represented by the process model including executing CV nodes of the process model by performing video stream processing represented by the CV nodes of the process model. The available CV nodes include a set of video pattern detection nodes, and a set of video pattern relation nodes defining a video grammar of relations between video patterns detectable by the video pattern detection nodes.
    Type: Application
    Filed: April 27, 2015
    Publication date: October 27, 2016
    Inventors: Adrian Corneliu Mos, Adrien Gaidon, Eleonora Vig
  • Patent number: 9443320
    Abstract: A tracking system and method are suited to tracking multiple of objects of different categories in a video sequence. A sequence of video frames is received and a set of windows is extracted from each frame in turn, based on a computed probability that the respective window contains an object, without reference to any specific category of object. For each of these windows, a feature representation is extracted. A trained detector for a selected category detects windows that constitute targets in that category, based on the respective feature representations. More than one detector can be used when there is more than one category of objects to be tracked. A target-specific appearance model is generated for each of the targets (e.g., learned or updated, if the target is present in a prior frame). The detected targets are tracked over one or more subsequent frames based on the target-specific appearance models of the targets.
    Type: Grant
    Filed: May 18, 2015
    Date of Patent: September 13, 2016
    Assignee: XEROX CORPORATION
    Inventors: Adrien Gaidon, Eleonora Vig
Narrow Results

Filter by US Classification