Patents by Inventor Benjamin Michael Glocker
Benjamin Michael Glocker 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).
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Patent number: 11710309Abstract: Camera or object pose calculation is described, for example, to relocalize a mobile camera (such as on a smart phone) in a known environment or to compute the pose of an object moving relative to a fixed camera. The pose information is useful for robotics, augmented reality, navigation and other applications. In various embodiments where camera pose is calculated, a trained machine learning system associates image elements from an image of a scene, with points in the scene's 3D world coordinate frame. In examples where the camera is fixed and the pose of an object is to be calculated, the trained machine learning system associates image elements from an image of the object with points in an object coordinate frame. In examples, the image elements may be noisy and incomplete and a pose inference engine calculates an accurate estimate of the pose.Type: GrantFiled: February 13, 2018Date of Patent: July 25, 2023Assignee: Microsoft Technology Licensing, LLCInventors: Jamie Daniel Joseph Shotton, Benjamin Michael Glocker, Christopher Zach, Shahram Izadi, Antonio Criminisi, Andrew William Fitzgibbon
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Publication number: 20180285697Abstract: Camera or object pose calculation is described, for example, to relocalize a mobile camera (such as on a smart phone) in a known environment or to compute the pose of an object moving relative to a fixed camera. The pose information is useful for robotics, augmented reality, navigation and other applications. In various embodiments where camera pose is calculated, a trained machine learning system associates image elements from an image of a scene, with points in the scene's 3D world coordinate frame. In examples where the camera is fixed and the pose of an object is to be calculated, the trained machine learning system associates image elements from an image of the object with points in an object coordinate frame. In examples, the image elements may be noisy and incomplete and a pose inference engine calculates an accurate estimate of the pose.Type: ApplicationFiled: February 13, 2018Publication date: October 4, 2018Inventors: Jamie Daniel Joseph Shotton, Benjamin Michael Glocker, Christopher Zach, Shahram Izadi, Antonio Criminisi, Andrew William Fitzgibbon
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Patent number: 9940553Abstract: Camera or object pose calculation is described, for example, to relocalize a mobile camera (such as on a smart phone) in a known environment or to compute the pose of an object moving relative to a fixed camera. The pose information is useful for robotics, augmented reality, navigation and other applications. In various embodiments where camera pose is calculated, a trained machine learning system associates image elements from an image of a scene, with points in the scene's 3D world coordinate frame. In examples where the camera is fixed and the pose of an object is to be calculated, the trained machine learning system associates image elements from an image of the object with points in an object coordinate frame. In examples, the image elements may be noisy and incomplete and a pose inference engine calculates an accurate estimate of the pose.Type: GrantFiled: February 22, 2013Date of Patent: April 10, 2018Assignee: Microsoft Technology Licensing, LLCInventors: Jamie Daniel Joseph Shotton, Benjamin Michael Glocker, Christopher Zach, Shahram Izadi, Antonio Criminisi, Andrew William Fitzgibbon
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Patent number: 9613298Abstract: Tracking using sensor data is described, for example, where a plurality of machine learning predictors are used to predict a plurality of complementary, or diverse, parameter values of a process describing how the sensor data arises. In various examples a selector selects which of the predicted values are to be used, for example, to control a computing device. In some examples the tracked parameter values are pose of a moving camera or pose of an object moving in the field of view of a static camera; in some examples the tracked parameter values are of a 3D model of a hand or other articulated or deformable entity. The machine learning predictors have been trained in series, with training examples being reweighted after training an individual predictor, to favor training examples on which the set of predictors already trained performs poorly.Type: GrantFiled: June 2, 2014Date of Patent: April 4, 2017Assignee: Microsoft Technology Licensing, LLCInventors: Abner Guzmán-Rivera, Pushmeet Kohli, Benjamin Michael Glocker, Jamie Daniel Joseph Shotton, Shahram Izadi, Toby Sharp, Andrew William Fitzgibbon
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Publication number: 20150347846Abstract: Tracking using sensor data is described, for example, where a plurality of machine learning predictors are used to predict a plurality of complementary, or diverse, parameter values of a process describing how the sensor data arises. In various examples a selector selects which of the predicted values are to be used, for example, to control a computing device. In some examples the tracked parameter values are pose of a moving camera or pose of an object moving in the field of view of a static camera; in some examples the tracked parameter values are of a 3D model of a hand or other articulated or deformable entity. The machine learning predictors have been trained in series, with training examples being reweighted after training an individual predictor, to favour training examples on which the set of predictors already trained performs poorly.Type: ApplicationFiled: June 2, 2014Publication date: December 3, 2015Applicant: Microsoft CorporationInventors: Abner GUZMÁN-RIVERA, Pushmeet KOHLI, Benjamin Michael GLOCKER, Jamie Daniel Joseph SHOTTON, Shahram IZADI, Toby SHARP, Andrew William FITZGIBBON
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Publication number: 20140241617Abstract: Camera or object pose calculation is described, for example, to relocalize a mobile camera (such as on a smart phone) in a known environment or to compute the pose of an object moving relative to a fixed camera. The pose information is useful for robotics, augmented reality, navigation and other applications. In various embodiments where camera pose is calculated, a trained machine learning system associates image elements from an image of a scene, with points in the scene's 3D world coordinate frame. In examples where the camera is fixed and the pose of an object is to be calculated, the trained machine learning system associates image elements from an image of the object with points in an object coordinate frame. In examples, the image elements may be noisy and incomplete and a pose inference engine calculates an accurate estimate of the pose.Type: ApplicationFiled: February 22, 2013Publication date: August 28, 2014Applicant: MICROSOFT CORPORATIONInventors: Jamie Daniel Joseph Shotton, Benjamin Michael Glocker, Christopher Zach, Shahram Izadi, Antonio Criminisi, Andrew William Fitzgibbon