Patents by Inventor Mark Kliger
Mark Kliger 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: 11861944Abstract: Video output is generated based on first video data that depicts the user performing an activity. Poses of the user during performance of the activity are compared with second video data that depicts an instructor performing the activity. Corresponding poses of the user's body and the instructor's body may be determined through comparison of the first and second video data. The video data is used to determine the rate of motion of the user and to generate video output in which a visual representation of the instructor moves at a rate similar to the that of the user. For example, video output generated based on an instructional fitness video may be synchronized so that movement of the presented instructor matches the rate of movement of the user performing an exercise, improving user comprehension and performance.Type: GrantFiled: September 25, 2019Date of Patent: January 2, 2024Assignee: AMAZON TECHNOLOGIES, INC.Inventors: Ido Yerushalmy, Ianir Ideses, Eli Alshan, Mark Kliger, Liza Potikha, Dotan Kaufman, Sharon Alpert, Eduard Oks, Noam Sorek
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Patent number: 11783542Abstract: Devices and techniques are generally described for three dimensional mesh generation. In various examples, first two-dimensional (2D) image data representing a human body may be received from a first image sensor. Second 2D image data representing the human body may be received from a second image sensor. A first pose parameter and a first shape parameter may be determined using a first three-dimensional (3D) mesh prediction model and the first 2D image data. A second pose parameter and a second shape parameter may be determined using a second 3D mesh prediction model and the second 2D image data. In various examples, an updated 3D mesh prediction model may be generated from the first 3D mesh prediction model based at least in part on a first difference between the first pose parameter and the second pose parameter and a second difference between the first shape parameter and the second shape parameter.Type: GrantFiled: September 29, 2021Date of Patent: October 10, 2023Assignee: AMAZON TECHNOLOGIES, INC.Inventors: Matan Goldman, Lior Fritz, Omer Meir, Imry Kissos, Yaar Harari, Eduard Oks, Mark Kliger
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Patent number: 11771863Abstract: Systems for assisting a user in performance of a meditation activity or another type of activity are described. The systems receive user input and sensor data indicating physiological values associated with the user. These values are used to determine a recommended type of activity and a length of time for the activity. While the user performs the activity, sensors are used to measure physiological values, and an output that is provided to the user is selected based on the measured physiological values. The output may be selected to assist the user in reaching target physiological values, such as a slower respiration rate. After completion of the activity, additional physiological values are used to determine the effectiveness of the activity and the output that was provided. The effectiveness of the activity and the output may be used to determine future recommendations and future output.Type: GrantFiled: December 11, 2019Date of Patent: October 3, 2023Assignee: AMAZON TECHNOLOGIES, INC.Inventors: Eli Alshan, Mark Kliger, Ido Yerushalmy, Liza Potikha, Dotan Kaufman, Ianir Ideses, Eduard Oks, Noam Sorek
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Publication number: 20220261574Abstract: Characteristics of a user's movement are evaluated based on performance of activities by a user within a field of view of a camera. Video data representing performance of a series of movements by the user is acquired by the camera. Pose data is determined based on the video data, the pose data representing positions of the user's body while performing the movements. The pose data is compared to a set of existing videos that correspond to known errors to identify errors performed by the user. The errors may be used to generate scores for various characteristics of the user's movement. Based on the errors, exercises or other activities to improve the movement of the user may be determined and included in an output presented to the user.Type: ApplicationFiled: February 16, 2021Publication date: August 18, 2022Inventors: EDUARD OKS, RIDGE CARPENTER, LAMARR SMITH, CLAIRE MCGOWAN, ELIZABETH REISMAN, IANIR IDESES, ELI ALSHAN, MARK KLIGER, MATAN GOLDMAN, LIZA POTIKHA, IDO YERUSHALMY, DOTAN KAUFMAN, GUY ADAM, OMER MEIR, LIOR FRITZ, IMRY KISSOS, GEORGY MELAMED, ERAN BORENSTEIN, SHARON ALPERT, NOAM SOREK
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Publication number: 20220167858Abstract: The present invention is for a method and system for pain classification and monitoring optionally in a subject that is an awake, semi-awake or sedated.Type: ApplicationFiled: February 16, 2022Publication date: June 2, 2022Inventors: Galit Zuckerman-Stark, Mark Kliger
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Patent number: 11259708Abstract: The present invention is for a method and system for pain classification and monitoring optionally in a subject that is an awake, semi-awake or sedated.Type: GrantFiled: August 3, 2020Date of Patent: March 1, 2022Assignee: Medasense Biometrics Ltd.Inventors: Galit Zuckerman-Stark, Mark Kliger
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Publication number: 20200359914Abstract: The present invention is for a method and system for pain classification and monitoring optionally in a subject that is an awake, semi-awake or sedated.Type: ApplicationFiled: August 3, 2020Publication date: November 19, 2020Inventors: Galit Zuckerman-Stark, Mark Kliger
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Patent number: 10743778Abstract: The present invention is for a method and system for pain classification and monitoring optionally in a subject that is an awake, semi-awake or sedated.Type: GrantFiled: November 11, 2016Date of Patent: August 18, 2020Assignee: Medasense Biometrics Ltd.Inventors: Galit Zuckerman-Stark, Mark Kliger
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Patent number: 10685446Abstract: A system, article, and method of recurrent semantic segmentation for image processing by factoring historical semantic segmentation.Type: GrantFiled: January 12, 2018Date of Patent: June 16, 2020Assignee: Intel CorporationInventors: Shahar Fleishman, Naomi Ken Korem, Mark Kliger
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Patent number: 10643382Abstract: Convolutional Neural Networks are applied to object meshes to allow three-dimensional objects to be analyzed. In one example, a method includes performing convolutions on a mesh, wherein the mesh represents a three-dimensional object of an image, the mesh having a plurality of vertices and a plurality of edges between the vertices, performing pooling on the convolutions of an edge of a mesh, and applying fully connected and loss layers to the pooled convolutions to provide metadata about the three-dimensional object.Type: GrantFiled: April 4, 2017Date of Patent: May 5, 2020Assignee: Intel CorporationInventors: Shahar Fleishman, Mark Kliger
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Patent number: 10573018Abstract: Techniques are provided for context-based 3D scene reconstruction employing fusion of multiple instances of an object within the scene. A methodology implementing the techniques according to an embodiment includes receiving 3D image frames of the scene, each frame associated with a pose of a depth camera, and creating a 3D reconstruction of the scene based on depth pixels that are projected and accumulated into a global coordinate system. The method may also include detecting objects, based on the 3D reconstruction, the camera pose and the image frames. The method may further include classifying the detected objects into one or more object classes; grouping two or more instances of objects in one of the object classes based on a measure of similarity of features between the object instances; and combining point clouds associated with each of the grouped object instances to generate a fused object.Type: GrantFiled: July 13, 2016Date of Patent: February 25, 2020Assignee: Intel CorporationInventors: Gershom Kutliroff, Shahar Fleishman, Mark Kliger
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Patent number: 10452789Abstract: Systems, apparatuses and/or methods may provide for generating a packing order of items within a container that consolidates the items into a reduced space. Items may be scanned with a three-dimensional (3D) imager, and models may be generated of the items based on the data from the 3D imager. The items may be located within minimal-volume enclosing bounding boxes, which may be analyzed to determine whether they may be merged together in one of their bounding boxes, or into a new bounding box that is spatially advantageous in terms of packing. If a combination of items is realizable and is determined to take up less space in a bounding box than the bounding boxes of the items considered separately, then they may be merged into a single bounding box. Thus, a spatially efficient packing sequence for a plurality of real objects may be generated to maximize packing efficiency.Type: GrantFiled: November 30, 2015Date of Patent: October 22, 2019Assignee: Intel CorporationInventors: Maoz Madmony, Shahar Fleishman, Mark Kliger, Gershom Kutliroff
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Patent number: 10373380Abstract: Techniques are provided for 3D analysis of a scene including detection, segmentation and registration of objects within the scene. The analysis results may be used to implement augmented reality operations including removal and insertion of objects and the generation of blueprints. An example method may include receiving 3D image frames of the scene, each frame associated with a pose of a depth camera, and creating a 3D reconstruction of the scene based on depth pixels that are projected and accumulated into a global coordinate system. The method may also include detecting objects, and associated locations within the scene, based on the 3D reconstruction, the camera pose and the image frames. The method may further include segmenting the detected objects into points of the 3D reconstruction corresponding to contours of the object and registering the segmented objects to 3D models of the objects to determine their alignment.Type: GrantFiled: February 18, 2016Date of Patent: August 6, 2019Assignee: Intel CorporationInventors: Gershom Kutliroff, Yaron Yanai, Shahar Fleishman, Mark Kliger
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Patent number: 10229542Abstract: Techniques are provided for 3D analysis of a scene including detection, segmentation and registration of objects within the scene. The analysis results may be used to implement augmented reality operations including removal and insertion of objects and the generation of blueprints. An example method may include receiving 3D image frames of the scene, each frame associated with a pose of a depth camera, and creating a 3D reconstruction of the scene based on depth pixels that are projected and accumulated into a global coordinate system. The method may also include detecting objects, and associated locations within the scene, based on the 3D reconstruction, the camera pose and the image frames. The method may further include segmenting the detected objects into points of the 3D reconstruction corresponding to contours of the object and registering the segmented objects to 3D models of the objects to determine their alignment.Type: GrantFiled: February 18, 2016Date of Patent: March 12, 2019Assignee: Intel CorporationInventors: Gershom Kutliroff, Yaron Yanai, Shahar Fleishman, Mark Kliger
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Publication number: 20190043203Abstract: A system, article, and method of recurrent semantic segmentation for image processing by factoring historical semantic segmentation.Type: ApplicationFiled: January 12, 2018Publication date: February 7, 2019Applicant: Intel CorporationInventors: Shahar FLEISHMAN, Naomi KEN KOREM, Mark KLIGER
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Publication number: 20180336439Abstract: An example apparatus for detecting novel data includes a discriminator trained using a generator to receive data to be classified. The discriminator may also be trained to classify the received data as novel data in response to detecting that the received data does not correspond to known categories of data.Type: ApplicationFiled: June 19, 2017Publication date: November 22, 2018Applicant: INTEL CORPORATIONInventors: Mark Kliger, Shahar Fleishman
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Publication number: 20180286120Abstract: Convolutional Neural Networks are applied to object meshes to allow three-dimensional objects to be analyzed. In one example, a method includes performing convolutions on a mesh, wherein the mesh represents a three-dimensional object of an image, the mesh having a plurality of vertices and a plurality of edges between the vertices, performing pooling on the convolutions of an edge of a mesh, and applying fully connected and loss layers to the pooled convolutions to provide metadata about the three-dimensional object.Type: ApplicationFiled: April 4, 2017Publication date: October 4, 2018Applicant: Intel CorporationInventors: Shahar Fleishman, Mark Kliger
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Patent number: 9911219Abstract: Techniques related to pose estimation for an articulated body are discussed. Such techniques may include extracting, segmenting, classifying, and labeling blobs, generating initial kinematic parameters that provide spatial relationships of elements of a kinematic model representing an articulated body, and refining the kinematic parameters to provide a pose estimation for the articulated body.Type: GrantFiled: June 24, 2015Date of Patent: March 6, 2018Assignee: Intel CorporationInventors: Shahar Fleishman, Mark Kliger, Alon Lerner
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Publication number: 20180018805Abstract: Techniques are provided for context-based 3D scene reconstruction employing fusion of multiple instances of an object within the scene. A methodology implementing the techniques according to an embodiment includes receiving 3D image frames of the scene, each frame associated with a pose of a depth camera, and creating a 3D reconstruction of the scene based on depth pixels that are projected and accumulated into a global coordinate system. The method may also include detecting objects, based on the 3D reconstruction, the camera pose and the image frames. The method may further include classifying the detected objects into one or more object classes; grouping two or more instances of objects in one of the object classes based on a measure of similarity of features between the object instances; and combining point clouds associated with each of the grouped object instances to generate a fused object.Type: ApplicationFiled: July 13, 2016Publication date: January 18, 2018Applicant: INTEL CORPORATIONInventors: Gershom Kutliroff, Shahar Fleishman, Mark Kliger
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Patent number: 9747717Abstract: Techniques related to non-rigid transformations for articulated bodies are discussed. Such techniques may include repeatedly selecting target positions for matching a kinematic model of an articulated body, generating virtual end-effectors for the kinematic model and corresponding to the target positions, generating an inverse kinematics problem including a Jacobian matrix, and determining a change in kinematic model parameters based on the inverse kinematics problem until a convergence is attained.Type: GrantFiled: June 24, 2015Date of Patent: August 29, 2017Assignee: Intel CorporationInventors: Shahar Fleishman, Mark Kliger, Alon Lerner