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公开(公告)号:US20220076385A1
公开(公告)日:2022-03-10
申请号:US17526714
申请日:2021-11-15
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Green Rosh K S , Bindigan Hariprasanna Pawan Prasad , Nikhil Krishnan , Sachin Deepak Lomte , Anmol Biswas
Abstract: A method for processing image data, may include: receiving at least one image; segregating the at least one image into at least one region, based on a requested noise reduction level; and denoising the at least one image by varying at least one control feature of the segregated at least one region by a neural network to achieve the requested noise reduction level.
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公开(公告)号:US20250069237A1
公开(公告)日:2025-02-27
申请号:US18946632
申请日:2024-11-13
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Abstract: A method for recognizing an action of at least one object in a plurality of images, includes obtaining a plurality of image frames by capturing at least one object on a ground plane; detecting a motion of the at least one object and a motion of the ground plane in each of the plurality of image frames; estimating a trajectory of the ground plane by tracking the motion of the ground plane; correcting the motion of the at least one object in each of the plurality of image frames based on the trajectory of the ground plane; and recognizing an action of the at least one object based on the corrected motion of the at least one object.
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公开(公告)号:US20240428620A1
公开(公告)日:2024-12-26
申请号:US18823150
申请日:2024-09-03
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Vishakha S R , Pawan Prasad BINDIGAN HARIPRASANNA , Green Rosh K S , Akula JAYAPRAKASH , Prateek KUKREJA
Abstract: Provided are a system and a method for recognizing non-line-of-sight human action, the method including receiving a plurality of image frames in a sequential order from an imaging device, wherein at least one of the plurality of image frames comprises at least one entity performing an action; identifying, based on the plurality of image frames, that a first partial portion of the action occurs within a field of view of the imaging device and a second partial portion of the action occurs outside the field of view of the imaging device; identifying a type of a motion which occurs during the action based on the first partial portion; extrapolating the motion based on the first partial portion, and generating a trajectory of the motion corresponding to the second partial portion of the action; and recognizing the human action from the type of the motion and the trajectory of the motion.
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公开(公告)号:US20240312176A1
公开(公告)日:2024-09-19
申请号:US18671412
申请日:2024-05-22
Applicant: Samsung Electronics Co., Ltd.
Inventor: Pawan Prasad BINDIGAN HARIPRASANNA , Green Rosh K S , Vishakha S R , Sungsoo CHOI , Hyuntaek WOO , Chaeeun LEE , Beomsu KIM
CPC classification number: G06V10/273 , G06V10/82 , G06V40/11
Abstract: A method performed by an electronic device for estimating a landmark point of a body part of subject by electronic device is provided. The method includes generating, by the electronic device, an initial coarse estimation of the landmark point of the body part using a light-weight deep neural network, determining, by the electronic device, an occluded region of the body part based on the generated initial coarse estimation of the landmark point using a segmentation mask, estimating, by the electronic device, the occlusion probability for the landmark point in the at least one occluded region and the generated initial coarse estimation, determining, by the electronic device, a correction factor for applying on the generated initial coarse estimation as a measure of the estimated occlusion probability, and selecting, by the electronic device, a pre-defined number of neural networks by applying the determined correction factor for processing the at least one occluded region and the generated initial coarse estimation to generate final estimation of the landmark point.
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公开(公告)号:US20220398700A1
公开(公告)日:2022-12-15
申请号:US17889988
申请日:2022-08-17
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Green Rosh K S , Nikhil Krishnan , Yash Harbhajanka , Badhisatwa Mandal
IPC: G06T5/00 , G06T7/13 , G06V10/82 , G06V10/774 , G06V10/776 , H04N5/235
Abstract: A method for enhancing media includes: receiving, by an electronic device, a media stream; performing, by the electronic device, an alignment of a plurality of frames of the media stream; correcting, by the electronic device, a brightness of the plurality of frames; selecting, by the electronic device, one of a first neural network, a second neural network, or a third neural network, by analyzing parameters of the plurality of frames having the corrected brightness, wherein the parameters include at least one of shot boundary detection and artificial light flickering; and generating, by the electronic device, an output media stream by processing the plurality of frames of the media stream using the selected one of the first neural network, the second neural network, or the third neural network.
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公开(公告)号:US20250046122A1
公开(公告)日:2025-02-06
申请号:US18907042
申请日:2024-10-04
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Vishakha S R , Bindigan Hariprasanna Pawan Prasad , Green Rosh K S , Akula Jayaprakash , Meghana Shankar , Prateek Kukreja , Shubham Mallik Thakur , Sagar Parmar , Mukesh Jha , Sungsoo Choi , Hyuntaek Woo , Chaeeun Lee , Beomsu Kim
IPC: G06V40/20 , A63F13/213 , A63F13/428 , G06F3/01 , G06V10/75 , G06V10/77
Abstract: There is provided a method and apparatus for performing gesture recognition in an electronic device, including: tracking a visible trajectory of a hand of a user from a plurality of frames captured by the electronic device, identifying, by the electronic device, a first frame where the hand of the user has gone out of a Field of View (FOV) of the electronic device, identifying the second frame where the hand of the user has come back into the FOV, predicting, using an Artificial Intelligence (AI) model, a trajectory of the hand of the user using one or more frames captured before the first frame, and one or more frames captured after the second frame, and recognizing at least one hand gesture performed during the visible trajectory of the hand of the user, and the predicted trajectory of the hand of the user.
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公开(公告)号:US20240273904A1
公开(公告)日:2024-08-15
申请号:US18646349
申请日:2024-04-25
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Bindigan Hariprasanna PAWAN PRASAD , Green Rosh K S , Vishakha S R , Lokesh Rayasandra BOREGOWDA
CPC classification number: G06V20/48 , G06T7/20 , G06T7/70 , G06V10/761 , G06T2207/20084
Abstract: There is provided a method and electronic device for generating high resolution peak action frame. The method includes receiving a low resolution (LR) image stream with high frame speed and a high resolution (HR) image stream with low frame speed and detecting at least one pose of at least one human in the LR image stream. The method further includes obtaining a LR peak action frame in the LR image stream based on the at least one pose and identifying a close HR frame from the HR image stream which is closest to the LR peak action frame. The method further includes fetching the close HR frame from the HR image stream which is closest to the obtained LR peak action frame or generating a HR peak action frame by blending the identified HR frame and the LR peak action frame.
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公开(公告)号:US20230377098A1
公开(公告)日:2023-11-23
申请号:US18230451
申请日:2023-08-04
Applicant: SAMSUNG ELECTRONICS CO., LTD.
IPC: G06T5/00
CPC classification number: G06T5/002 , G06T2207/20104 , G06T2207/10016 , G06T2207/20084
Abstract: A method 300B includes detecting a user input indicative of a trigger to modify the artifact of the image displayed at a user interface of an electronic device 100. Furthermore, the method 300B includes determining an artifact modification parameter based on a characteristic of the user input. Furthermore, the method 300B includes modifying the artifact in the image based on the artifact modification parameter.
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公开(公告)号:US11563898B2
公开(公告)日:2023-01-24
申请号:US17275422
申请日:2019-09-11
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Mandakinee Singh Patel , Green Rosh K S , Anmol Biswas , Bindigan Hariprasanna Pawan Prasad
Abstract: Apparatus and methods for generating High Dynamic Range (HDR) media, based on multi-stage compensation of motion in a captured scene is disclosed in the embodiments herein. Embodiments herein relates to the field of image processing devices suitable for processing two or more images of different exposures and more particularly to apparatus and methods for generating a High Dynamic Range (HDR) media, based on a multi-stage compensation of motion in a captured scene. The apparatus is configured to correct exposure alignment error and media registration error from a registered plurality of media frames comprising a plurality of exposure levels corresponding to the captured scene. The apparatus is configured to remove a plurality of false ghost artefacts in the plurality of media frames. The apparatus is configured to generate the HDR media, based on a generated ghost map.
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公开(公告)号:US20220318961A1
公开(公告)日:2022-10-06
申请号:US17842309
申请日:2022-06-16
Applicant: Samsung Electronics Co., Ltd.
Inventor: Pawan Prasad BINDIGAN HARIPRASANNA , Saikat Kumar DAS , Green Rosh K S , Lokesh Rayasandra BOREGOWDA , Balvinder SINGH , Venkat Ramana PEDDIGARI , Alok Shankarlal SHUKLA
IPC: G06T5/00 , G06T3/40 , G06T5/20 , G06V10/776 , G06V10/764
Abstract: Embodiments herein provide a method for removing an artefact in a high resolution image by an electronic device (100). The method includes receiving the high resolution image comprising the artefact. Further, the method includes downscaling the high resolution image into a plurality of lower resolution images. Further, the method includes removing the artefact from the plurality of lower resolution images by applying at least one first machine learning model from a plurality of machine learning models on the plurality of lower resolution images. Further, the method includes generating a high resolution image free from the artefact by applying at least one second machine learning model from the plurality of machine learning models on an output from the at least one first machine learning model. The output from each of the machine learning model comprises a low resolution image free from the artefact.
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