Patents by Inventor Chun-Te Chu

Chun-Te Chu 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: 10650226
    Abstract: Systems and methods for identifying a false representation of a human face are provided. In one example, a method for identifying a false representation of a human face includes receiving one or more data streams captured by one or more sensors sensing a candidate face. In a plurality of stages that each comprises a different analysis, one or more of the data streams are analyzed, and the stages comprise determining whether a plurality of candidate face depth points lies on a single flat plane or a curving plane. Based at least in part on determining that the plurality of candidate face depth points lies on the single flat plane, an indication of the false representation of the human face is outputted.
    Type: Grant
    Filed: June 19, 2018
    Date of Patent: May 12, 2020
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Chun-Te Chu, Michael J. Conrad, Dijia Wu, Jinyu Li
  • Patent number: 10452935
    Abstract: Examples are disclosed herein that relate to detecting spoofed human faces. One example provides a computing device comprising a processor configured to compute a first feature distance between registered image data of a human face in a first spectral region and test image data of the human face in the first spectral region, compute a second feature distance between the registered image data and test image data of the human face in a second spectral region, compute a test feature distance between the test image data in the first spectral region and the test image data in the second spectral region, determine, based on a predetermined relationship, whether the human face to which the test image data in the first and second spectral regions corresponds is a real human face or a spoofed human face, and modify a behavior of the computing device.
    Type: Grant
    Filed: October 30, 2015
    Date of Patent: October 22, 2019
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Jinyu Li, Fang Wen, Yichen Wei, Michael John Conrad, Chun-Te Chu, Aamir Jawaid
  • Patent number: 10181090
    Abstract: A technique for multi-camera object tracking is disclosed that preserves privacy of imagery from each camera or group of cameras. This technique uses secure multi-party computation to compute a distance metric across data from multiple cameras without revealing any information to operators of the cameras except whether or not an object was observed by both cameras. This is achieved by a distance metric learning technique that reduces the computing complexity of secure computation while maintaining object identification accuracy.
    Type: Grant
    Filed: April 20, 2018
    Date of Patent: January 15, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Chun-Te Chu, Jaeyeon Jung, Zicheng Liu, Ratul Mahajan
  • Publication number: 20180307895
    Abstract: Systems and methods for identifying a false representation of a human face are provided. In one example, a method for identifying a false representation of a human face includes receiving one or more data streams captured by one or more sensors sensing a candidate face. In a plurality of stages that each comprises a different analysis, one or more of the data streams are analyzed, and the stages comprise determining whether a plurality of candidate face depth points lies on a single flat plane or a curving plane. Based at least in part on determining that the plurality of candidate face depth points lies on the single flat plane, an indication of the false representation of the human face is outputted.
    Type: Application
    Filed: June 19, 2018
    Publication date: October 25, 2018
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Chun-Te Chu, Michael J. Conrad, Dijia Wu, Jinyu Li
  • Publication number: 20180285668
    Abstract: Examples are disclosed herein that relate to detecting spoofed human faces. One example provides a computing device comprising a processor configured to compute a first feature distance between registered image data of a human face in a first spectral region and test image data of the human face in the first spectral region, compute a second feature distance between the registered image data and test image data of the human face in a second spectral region, compute a test feature distance between the test image data in the first spectral region and the test image data in the second spectral region, determine, based on a predetermined relationship, whether the human face to which the test image data in the first and second spectral regions corresponds is a real human face or a spoofed human face, and modify a behavior of the computing device.
    Type: Application
    Filed: October 30, 2015
    Publication date: October 4, 2018
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Jinyu Li, Fang Wen, Yichen Wei, Michael John Conrad, Chun-Te Chu, Aamir Jawaid
  • Publication number: 20180239985
    Abstract: A technique for multi-camera object tracking is disclosed that preserves privacy of imagery from each camera or group of cameras. This technique uses secure multi-party computation to compute a distance metric across data from multiple cameras without revealing any information to operators of the cameras except whether or not an object was observed by both cameras. This is achieved by a distance metric learning technique that reduces the computing complexity of secure computation while maintaining object identification accuracy.
    Type: Application
    Filed: April 20, 2018
    Publication date: August 23, 2018
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Chun-Te Chu, Jaeyeon Jung, Zicheng Liu, Ratul Mahajan
  • Patent number: 10007839
    Abstract: Systems and methods for identifying a false representation of a human face are provided. In one example, a method for identifying a false representation of a human face includes receiving a plurality of different data streams captured by a respective plurality of sensors of differing sensor types sensing a candidate face. In a cascading plurality of stages, one or more of the different data streams are analyzed, wherein each of the stages comprises a different analysis. In one of the cascading plurality of stages, the method determines that one or more of the different data streams corresponds to a false representation of the human face. Based on determining that one or more of the different data streams corresponds to a false representation of a human face, an indication of the false representation is outputted.
    Type: Grant
    Filed: February 27, 2017
    Date of Patent: June 26, 2018
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Chun-Te Chu, Michael J. Conrad, Dijia Wu, Jinyu Li
  • Patent number: 9977991
    Abstract: A technique for multi-camera object tracking is disclosed that preserves privacy of imagery from each camera or group of cameras. This technique uses secure multi-party computation to compute a distance metric across data from multiple cameras without revealing any information to operators of the cameras except whether or not an object was observed by both cameras. This is achieved by a distance metric learning technique that reduces the computing complexity of secure computation while maintaining object identification accuracy.
    Type: Grant
    Filed: April 22, 2015
    Date of Patent: May 22, 2018
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Chun-Te Chu, Jaeyeon Jung, Zicheng Liu, Ratul Mahajan
  • Patent number: 9704038
    Abstract: Examples are disclosed herein that relate to eye tracking based on two-dimensional image data. One example provides, on a computing device, a method of tracking an eye. The method includes receiving image data from an image sensor, detecting a face of the user in the image data, locating the eye in a region of the face in the image data to obtain an eye image, normalizing one or more of a scale and an illumination of the eye image, fitting an ellipse to an iris of the eye in the eye image, and outputting a determination of an eye gaze direction based upon the ellipse fitted.
    Type: Grant
    Filed: January 7, 2015
    Date of Patent: July 11, 2017
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Dijia Wu, Michael J. Conrad, Chun-Te Chu, Geoffrey John Hulten
  • Publication number: 20170169284
    Abstract: Systems and methods for identifying a false representation of a human face are provided. In one example, a method for identifying a false representation of a human face includes receiving a plurality of different data streams captured by a respective plurality of sensors of differing sensor types sensing a candidate face. In a cascading plurality of stages, one or more of the different data streams are analyzed, wherein each of the stages comprises a different analysis. In one of the cascading plurality of stages, the method determines that one or more of the different data streams corresponds to a false representation of the human face. Based on determining that one or more of the different data streams corresponds to a false representation of a human face, an indication of the false representation is outputted.
    Type: Application
    Filed: February 27, 2017
    Publication date: June 15, 2017
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Chun-Te Chu, Michael J. Conrad, Dijia Wu, Jinyu Li
  • Patent number: 9582724
    Abstract: Systems and methods for identifying a false representation of a human face are provided. In one example, a method for identifying a false representation of a human face includes receiving a plurality of different data streams captured by a respective plurality of sensors of differing sensor types sensing a candidate face. In a cascading plurality of stages, one or more of the different data streams are analyzed, wherein each of the stages comprises a different analysis. In one of the cascading plurality of stages, the method determines that one or more of the different data streams corresponds to a false representation of the human face. Based on determining that one or more of the different data streams corresponds to a false representation of a human face, an indication of the false representation is outputted.
    Type: Grant
    Filed: January 27, 2016
    Date of Patent: February 28, 2017
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Chun-Te Chu, Michael J. Conrad, Dijia Wu, Jinyu Li
  • Publication number: 20160196465
    Abstract: Examples are disclosed herein that relate to eye tracking based on two-dimensional image data. One example provides, on a computing device, a method of tracking an eye. The method includes receiving image data from an image sensor, detecting a face of the user in the image data, locating the eye in a region of the face in the image data to obtain an eye image, normalizing one or more of a scale and an illumination of the eye image, fitting an ellipse to an iris of the eye in the eye image, and outputting a determination of an eye gaze direction based upon the ellipse fitted.
    Type: Application
    Filed: January 7, 2015
    Publication date: July 7, 2016
    Inventors: Dijia Wu, Michael J. Conrad, Chun-Te Chu, Geoffrey John Hulten
  • Publication number: 20160140406
    Abstract: Systems and methods for identifying a false representation of a human face are provided. In one example, a method for identifying a false representation of a human face includes receiving a plurality of different data streams captured by a respective plurality of sensors of differing sensor types sensing a candidate face. In a cascading plurality of stages, one or more of the different data streams are analyzed, wherein each of the stages comprises a different analysis. In one of the cascading plurality of stages, the method determines that one or more of the different data streams corresponds to a false representation of the human face. Based on determining that one or more of the different data streams corresponds to a false representation of a human face, an indication of the false representation is outputted.
    Type: Application
    Filed: January 27, 2016
    Publication date: May 19, 2016
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Chun-Te Chu, Michael J. Conrad, Dijia Wu, Jinyu Li
  • Publication number: 20160048736
    Abstract: Systems and methods for identifying a false representation of a human face are provided. In one example, a method for identifying a false representation of a human face includes receiving a plurality of different data streams captured by a respective plurality of sensors of differing sensor types sensing a candidate face. In a cascading plurality of stages, one or more of the different data streams are analyzed, wherein each of the stages comprises a different analysis. In one of the cascading plurality of stages, the method determines that one or more of the different data streams corresponds to a false representation of the human face. Based on determining that one or more of the different data streams corresponds to a false representation of a human face, an indication of the false representation is outputted.
    Type: Application
    Filed: August 12, 2014
    Publication date: February 18, 2016
    Inventors: Chun-Te Chu, Michael J. Conrad, Dijia Wu, Jinyu Li
  • Patent number: 9251427
    Abstract: Systems and methods for identifying a false representation of a human face are provided. In one example, a method for identifying a false representation of a human face includes receiving a plurality of different data streams captured by a respective plurality of sensors of differing sensor types sensing a candidate face. In a cascading plurality of stages, one or more of the different data streams are analyzed, wherein each of the stages comprises a different analysis. In one of the cascading plurality of stages, the method determines that one or more of the different data streams corresponds to a false representation of the human face. Based on determining that one or more of the different data streams corresponds to a false representation of a human face, an indication of the false representation is outputted.
    Type: Grant
    Filed: August 12, 2014
    Date of Patent: February 2, 2016
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Chun-Te Chu, Michael J. Conrad, Dijia Wu, Jinyu Li
  • Publication number: 20150242760
    Abstract: Machine learning may be personalized to individual users of computing devices, and can be used to increase machine learning prediction accuracy and speed, and/or reduce memory footprint. Personalizing machine learning can include hosting, by a computing device, a consensus machine learning model and collecting information, locally by the computing device, associated with an application executed by the client device. Personalizing machine learning can also include modifying the consensus machine learning model accessible by the application based, at least in part, on the information collected locally by the client device. Modifying the consensus machine learning model can generate a personalized machine learning model. Personalizing machine learning can also include transmitting the personalized machine learning model to a server that updates the consensus machine learning model.
    Type: Application
    Filed: February 21, 2014
    Publication date: August 27, 2015
    Applicant: Microsoft Corporation
    Inventors: Xu Miao, Chun-Te Chu
  • Publication number: 20150227814
    Abstract: A technique for multi-camera object tracking is disclosed that preserves privacy of imagery from each camera or group of cameras. This technique uses secure multi-party computation to compute a distance metric across data from multiple cameras without revealing any information to operators of the cameras except whether or not an object was observed by both cameras. This is achieved by a distance metric learning technique that reduces the computing complexity of secure computation while maintaining object identification accuracy.
    Type: Application
    Filed: April 22, 2015
    Publication date: August 13, 2015
    Inventors: Chun-Te Chu, Jaeyeon Jung, Zicheng Liu, Ratul Mahajan
  • Publication number: 20140184803
    Abstract: A technique for multi-camera object tracking is disclosed that preserves privacy of imagery from each camera or group of cameras. This technique uses secure multi-party computation to compute a distance metric across data from multiple cameras without revealing any information to operators of the cameras except whether or not an object was observed by both cameras. This is achieved by a distance metric learning technique that reduces the computing complexity of secure computation while maintaining object identification accuracy.
    Type: Application
    Filed: December 31, 2012
    Publication date: July 3, 2014
    Applicant: MICROSOFT CORPORATION
    Inventors: Chun-Te Chu, Jaeyeon Jung, Zicheng Liu, Ratul Mahajan