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公开(公告)号:US11263751B2
公开(公告)日:2022-03-01
申请号:US16666225
申请日:2019-10-28
Applicant: Samsung Electronics Co., Ltd.
Inventor: Sujoy Saha , Karthik Srinivasan , Sourabh Singh Yadav , Suhas Shantaraja Palasamudram , Venkat Ramana Peddigari , Pradeep Kumar Sk , Pranav P Deshpande , Akankshya Kar
Abstract: A method for real-time semantic image segmentation using a monocular event-based sensor includes capturing a scene using a red, green, blue (RGB) sensor to obtain a plurality of RGB frames and an event sensor to obtain event data corresponding to each of the plurality of RGB frames, performing object labeling for objects in a first RGB frame among the plurality of RGB frames by identifying one or more object classes, obtaining an event velocity of the scene by fusing the event data corresponding to the first RGB frame and at least one subsequent RGB frame among the plurality of RGB frames, determining whether the event velocity is greater than a predefined threshold, and performing object labeling for objects in the at least one subsequent RGB frame based on the determination.
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公开(公告)号:US20230377160A1
公开(公告)日:2023-11-23
申请号:US18198023
申请日:2023-05-16
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Rajat Kumar JAIN , Aditi Singhal , Sujoy Saha , Rajas Jayant Joshi , Amita Badhwar , Mansi Singh , Lokesh Rayasandra Boregowda
CPC classification number: G06T7/11 , G06F3/011 , G06T15/80 , G06T15/40 , G06T5/002 , G06T5/20 , G06T7/50 , G06T17/00 , G06T2207/10028 , G06T2207/20084 , G06T2207/20081
Abstract: There is provided a method for segmenting a point cloud by an electronic device. The method includes receiving the point cloud including colorless data and/or featureless data. Further, the method includes determining a normal vector for the received point cloud and/or a spatial feature for the received point cloud. Further, the method includes segmenting the point cloud based on the at least one of one or more normal vectors and one or more spatial features.
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公开(公告)号:US12154226B2
公开(公告)日:2024-11-26
申请号:US17948863
申请日:2022-09-20
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Sujoy Saha , Mahantesh Mallappa Ambi , Rajat Kumar Jain , Amita Badhwar , Aditi Singhal , Rakesh Abothula , Lokesh Rayasandra Boregowda
Abstract: A method for generating a three-dimensional (3D) model of an object includes receiving a two-dimensional (2D) view of at least one object as an input, measuring geometrical shape coordinates of the at least one object from the input, identifying texture parameters of the at least one object from the input, predicting geometrical shape coordinates and texture parameters of occluded portions of the at least one object in the 2D view by processing the measured geometrical shape coordinates of the at least one object, the identified texture parameters of the at least one object, and the occluded portions of the at least one object, and generating a 3D model of the at least one object by mapping the measured geometrical shape coordinates and the identified texture parameters to the predicted geometrical shape coordinates and the predicted texture parameters of the occluded portions of the at least one object.
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公开(公告)号:US20230012372A1
公开(公告)日:2023-01-12
申请号:US17948863
申请日:2022-09-20
Applicant: Samsung Electronics Co., Ltd.
Inventor: Sujoy Saha , Mahantesh Mallappa Ambi , Rajat Kumar Jain , Amita Badhwar , Aditi Singhal , Rakesh Abothula , Lokesh Rayasandra Boregowda
Abstract: A method for generating a three-dimensional (3D) model of an object includes receiving a two-dimensional (2D) view of at least one object as an input, measuring geometrical shape coordinates of the at least one object from the input, identifying texture parameters of the at least one object from the input, predicting geometrical shape coordinates and texture parameters of occluded portions of the at least one object in the 2D view by processing the measured geometrical shape coordinates of the at least one object, the identified texture parameters of the at least one object, and the occluded portions of the at least one object, and generating a 3D model of the at least one object by mapping the measured geometrical shape coordinates and the identified texture parameters to the predicted geometrical shape coordinates and the predicted texture parameters of the occluded portions of the at least one object.
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