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公开(公告)号：US20240163554A1
公开(公告)日：2024-05-16
申请号：US17988092
申请日：2022-11-16
Applicant: Black Sesame Technologies Inc.
Inventor： Jiaoyang Yao , Fangwen Tu , Bo Li
IPC: H04N23/67 , G01S17/86 , G01S17/894 , G06T7/277 , G06T7/521 , H04N23/611
CPC classification number: H04N23/671 , G01S17/86 , G01S17/894 , G06T7/277 , G06T7/521 , H04N23/611 , H04N23/675 , G06T2207/10024 , G06T2207/10028 , G06T2207/10048 , G06T2207/20021 , G06T2207/30196
Abstract: The invention discloses an active auto-focus tracking system using a time-of-flight (ToF) depth sensor. The ToF sensor serves as a rangefinder and also provides environmental depth information. The active auto-focus system includes a compressive tracking algorithm to track the movement of an object. The active auto-focus tracking system can acquire subject depth information regardless of various lighting conditions, subject positions, and visual patterns. Moreover, the system can perform an improved acquisition of focusing distance in both normal and low-level lighting conditions.
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公开(公告)号：US20230237816A1
公开(公告)日：2023-07-27
申请号：US17586724
申请日：2022-01-27
Applicant: Black Sesame Technologies Inc.
Inventor： Zi Sian Wong , Bo Li
CPC classification number: G06V20/625 , G06V20/582 , G06N20/20
Abstract: Methods, systems, and apparatuses, including computer programs encoded on computer storage media, for generating a prediction of at least a text and a particular type associated with an object are described in this specification. A first model output is generated by using a first machine learning model to process input data including one or more objects. The first model output identifies an existence of a particular object in the input data and specifies characteristics of the particular object. A type of the particular object is determined based on the specified characteristics. The type comprises a single-row type and a multi-row type. A single-row representation of the particular object is generated. A second model output is generated by processing the single-row representation. The second model output comprises a prediction of characters corresponding to the particular vehicle license plate.
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公开(公告)号：US20230083896A1
公开(公告)日：2023-03-16
申请号：US17474774
申请日：2021-09-14
Applicant: Black Sesame Technologies Inc.
Inventor： Fangwen Tu , Bo Li
Abstract: The present invention discloses a system for precise representation of object segmentation with multi-modal input for real-time video applications. The multi-modal segmentation system takes advantage of optical, temporal as well as spatial information to enhance the segmentation for AR and VR or other entrainment purpose with accurate details. The system can segment foreground objects such as human and salient objects within a video frame and allows locating object-of-interest for multiple-purposes.
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公开(公告)号：US20230035671A1
公开(公告)日：2023-02-02
申请号：US17376027
申请日：2021-07-14
Applicant: Black Sesame Technologies Inc.
Inventor： Tiecheng Wu , Bo Li
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a depth image, comprising obtaining data representing a first image generated by a first sensor and a second image generated by a second sensor, wherein each of the first and second images includes a plurality of pixels; determining, for each pixel of the plurality of pixels included in the first image, whether the pixel is a boundary pixel associated with a boundary of an object that is represented in the first image; determining, from a plurality of candidate penalty values and for each pixel in the first image, an optimized penalty value for the pixel; generating an optimized cost function for the first image based on the optimized penalty values for the plurality of pixels; and generating a depth image for the first image based on the optimized cost function.
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公开(公告)号：US20240311964A1
公开(公告)日：2024-09-19
申请号：US18121884
申请日：2023-03-15
Applicant: Black Sesame Technologies Inc.
Inventor： Bo Li
CPC classification number: G06T3/4076 , G06V10/25 , G06V10/44 , G06V10/56 , G06V10/761 , G06V10/82
Abstract: The invention discloses an image field of view extension using camera images of various quality and different overlapping field of views. By using a learning algorithm, the invention compares common points between the two images and makes calculations online and offline to a low-resolution, larger image so that the final image with a large field of view and high resolution. The invention provides strong adaptive capabilities to different input images while still providing a quality final image.
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Patent Agency Ranking
公开(公告)号：US20230083014A1
公开(公告)日：2023-03-16
申请号：US17475031
申请日：2021-09-14
Applicant: Black Sesame Technologies Inc.
Inventor： Jiaoyang Yao , Fangwen Tu , Bo Li
IPC: G06T5/50
Abstract: A method of depth estimation, including, receiving an image frame, determining a relative depth map based on the image frame, receiving a sparse depth frame, preprocessing the sparse depth frame, determining a scale-adjusted relative depth map based on the relative depth map and the preprocessed sparse depth frame and fusing the relative depth map and the scale-adjusted relative depth map to produce an absolute depth map.
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公开(公告)号：US20240153099A1
公开(公告)日：2024-05-09
申请号：US17978430
申请日：2022-11-01
Applicant: Black Sesame Technologies Inc.
Inventor： Xibeijia Guan , Tiecheng Wu , Bo Li
CPC classification number: G06T7/194 , G06V10/25 , G06V10/267 , G06T2207/20132
Abstract: The invention discloses a system for image segmentation for detecting an object. More particularly, the system performs two-stage segmentation on the object in the image to generate an enhanced image. The first stage is the object detection, followed by a second stage including segmentation. The invention segments the object from a background of the image to create an enhanced image.
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公开(公告)号：US11961249B2
公开(公告)日：2024-04-16
申请号：US17376027
申请日：2021-07-14
Applicant: Black Sesame Technologies Inc.
Inventor： Tiecheng Wu , Bo Li
CPC classification number: G06T7/55 , G06N20/00 , G06T5/70 , G06T2207/20081
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a depth image, comprising obtaining data representing a first image generated by a first sensor and a second image generated by a second sensor, wherein each of the first and second images includes a plurality of pixels; determining, for each pixel of the plurality of pixels included in the first image, whether the pixel is a boundary pixel associated with a boundary of an object that is represented in the first image; determining, from a plurality of candidate penalty values and for each pixel in the first image, an optimized penalty value for the pixel; generating an optimized cost function for the first image based on the optimized penalty values for the plurality of pixels; and generating a depth image for the first image based on the optimized cost function.
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公开(公告)号：US12190641B2
公开(公告)日：2025-01-07
申请号：US17474965
申请日：2021-09-14
Applicant: Black Sesame Technologies Inc.
IPC: G06K9/00 , G06F18/25 , G06V10/25 , G06V10/26 , G06V10/764 , G06V10/80 , G06V10/82 , G06V20/20 , G06V40/16 , G06V40/40
Abstract: The present invention discloses a liveliness detection technique. The technique is described for identifying facial attributes. The technique identifies the presented face in the image as real or deceptive. The system and method includes identifying the facial attributes and utilizing a multi task learning network. The neural network includes segmentation and classification functionalities. The final output is used to get pixel level semantic information and high level semantic information.
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公开(公告)号：US12046054B2
公开(公告)日：2024-07-23
申请号：US17586724
申请日：2022-01-27
Applicant: Black Sesame Technologies Inc.
Inventor： Zi Sian Wong , Bo Li
CPC classification number: G06V20/625 , G06N20/20 , G06V20/582
Abstract: Methods, systems, and apparatuses, including computer programs encoded on computer storage media, for generating a prediction of at least a text and a particular type associated with an object are described in this specification. A first model output is generated by using a first machine learning model to process input data including one or more objects. The first model output identifies an existence of a particular object in the input data and specifies characteristics of the particular object. A type of the particular object is determined based on the specified characteristics. The type comprises a single-row type and a multi-row type. A single-row representation of the particular object is generated. A second model output is generated by processing the single-row representation. The second model output comprises a prediction of characters corresponding to the particular vehicle license plate.
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