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公开(公告)号：US11875599B2
公开(公告)日：2024-01-16
申请号：US17393408
申请日：2021-08-04
Applicant: UBTECH ROBOTICS CORP LTD
Inventor： Yusheng Zeng , Yepeng Liu , Jun Cheng , Jianxin Pang , Jing Gu
IPC: G06V40/16 , G06V10/46 , G06V10/98 , G06N3/08 , G06F18/214 , G06F18/2431 , G06N3/045
CPC classification number: G06V40/161 , G06F18/214 , G06F18/2431 , G06N3/045 , G06N3/08 , G06V10/462 , G06V10/993
Abstract: A method for detecting blurriness of a human face in an image includes: performing a face detection in a target image; when a human face is detected in the target image, cropping the human face from the target image to obtain a face image and inputting the face image to a first neural network model to perform preliminary detection on a blurriness of the human face in the face image to obtain a preliminary detection result; and when the preliminary detection result meets a deep detection condition, inputting the face image to a second neural network model to perform deep detection on the blurriness of the human face in the face image to obtain a deep detection result.
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2.发明申请公开(公告)号：US20220198224A1
公开(公告)日：2022-06-23
申请号：US17510415
申请日：2021-10-26
Applicant: UBTECH ROBOTICS CORP LTD
Inventor： Hanliu Wang , Jun Cheng , Jianxin Pang
Abstract: A backlight face recognition method, a terminal device using the same, and a computer readable storage medium are provided. The method includes: performing a face detection on each original face image in an original face image sample set to obtain a face frame corresponding to the original face image; capturing the corresponding original face images from the original face image sample set, and obtaining a new face image containing background pixels corresponding to the captured original face images from the original face image sample set; preprocessing all the obtained new face images to obtain a backlight sample set and a normal lighting sample set; and training a convolutional neural network using the backlight sample set and the normal lighting sample set until the convolutional neural network reaches a preset stopping condition. The trained convolutional neural network will improve the accuracy of face recognition in complex background and strong light.
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公开(公告)号：US20220068109A1
公开(公告)日：2022-03-03
申请号：US17138944
申请日：2020-12-31
Applicant: UBTECH ROBOTICS CORP LTD
Inventor： Yusheng Zeng , Yepeng Liu , Jun Cheng , Jianxin Pang , Youjun Xiong
Abstract: A mask wearing status alarming method, a mobile device, and a computer readable storage medium are provided. The method includes: performing a face detection on an image to determine face areas each including a target determined as a face; determining a mask wearing status of the target in each face area; confirming the mask wearing status of the target in each face area using a trained face confirmation model to remove the face areas comprising the target being mistakenly determined as the face and determining a face pose in each of the remaining face areas to remove the face areas with the face pose not meeting a preset condition, in response to determining the mask wearing status as a not-masked-well status or a unmasked status; and releasing an alert corresponding to the mask wearing status of the target in each of the remaining face areas.
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公开(公告)号：US11074450B2
公开(公告)日：2021-07-27
申请号：US16726833
申请日：2019-12-25
Applicant: UBTECH ROBOTICS CORP LTD
Abstract: The present disclosure provides a picture hook identification method as well as an apparatus and a terminal device using the same. The method includes; determining geometric parameter(s) of an identification object based on image(s) collected b a camera and internal parameter(s) of the camera; comparing the geometric parameters of the identification object with geometric parameter(s) of a target picture book; and determining the identification object as the target picture book, if a difference between the geometric parameters of the identification object and the geometric parameters of the target picture book is within a preset range. In this manner, the target picture book is further filtered by matching the geometric parameters, which can reduce misidentification to improve the accuracy of identifying the picture book.
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公开(公告)号：US12277801B2
公开(公告)日：2025-04-15
申请号：US17566734
申请日：2021-12-31
Applicant: UBTECH ROBOTICS CORP LTD
Inventor： Chenghao Qian , Miaochen Guo , Jun Cheng , Jianxin Pang
Abstract: A gesture recognition method includes: acquiring a target image containing a gesture to be recognized; inputting the target image to a gesture recognition model that has a first sub-model, a second sub-model, and a third sub-model, the first sub-model is to determine a gesture category and a gesture center point, the second sub-model is to determine an offset of the gesture center point, and the third sub-model is to determine a length and a width of a bounding box for the gesture to be recognized; acquiring an output result from the gesture recognition model, the output result includes the gesture category, the gesture center point, and the offset of the gesture center point, and the length and the width of the bounding box; and determining the gesture category and a position of the bounding box of the gesture to be recognized according to the output result.
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Patent Agency Ranking
公开(公告)号：US11850747B2
公开(公告)日：2023-12-26
申请号：US17112569
申请日：2020-12-04
Applicant: UBTECH ROBOTICS CORP LTD
Inventor： Miaochen Guo , Jun Cheng , Jingtao Zhang , Shuping Hu , Dong Wang , Jianxin Pang , Youjun Xiong
CPC classification number: B25J9/161 , B25J9/1697 , B25J19/023 , G06N3/08
Abstract: The present disclosure provides an action imitation method as well as a robot and a computer readable storage medium using the same. The method includes: collecting a plurality of action images of a to-be-imitated object; processing the action images through a pre-trained convolutional neural network to obtain a position coordinate set of position coordinates of a plurality of key points of each of the action images; calculating a rotational angle of each of the linkages of the to-be-imitated object based on the position coordinate sets of the action images; and controlling a robot to move according to the rotational angle of each of the linkages of the to-be-imitated object. In the above-mentioned manner, the rotational angle of each linkage of the to-be-imitated object can be obtained by just analyzing and processing the images collected by an ordinary camera without the help of high-precision depth camera.
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公开(公告)号：US11631192B2
公开(公告)日：2023-04-18
申请号：US17107860
申请日：2020-11-30
Applicant: UBTECH ROBOTICS CORP LTD
Inventor： Shuping Hu , Jun Cheng , Jingtao Zhang , Miaochen Guo , Dong Wang , Jianxin Pang , Youjun Xiong
Abstract: A robot climbing control method is disclosed. The method obtains an RGB color image and a depth image of stairs, extracts an outline of a target object of a target step on the stairs from the RGB color image, determines relative position information of the robot and the target step according to the depth image and the outline of the target object, and controls the robot to climb the target step according to the relative position information. The embodiment of the present disclosure allows the robot to effectively adjust postures and forward directions on any size of and non-standardized stairs and avoids the deviation of the walking direction, thereby improving the effectiveness and safety of the stair climbing of the robot.
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公开(公告)号：US20220375106A1
公开(公告)日：2022-11-24
申请号：US17866574
申请日：2022-07-18
Applicant: UBTECH ROBOTICS CORP LTD
Inventor： Shuping Hu , Jun Cheng , Jingtao Zhang , Miaochen Guo , Dong Wang , Zaiwang Gu , Jianxin Pang
Abstract: A method includes: performing target detection on a current image to obtain detection information of a plurality of detected targets; obtaining position prediction information of each of a plurality of tracked targets and a number of times of tracking losses of targets from tracking information of each of the tracked targets, and determining a first matching threshold for each of the tracked targets according to the number of times of tracking losses of targets; calculating a motion matching degree between each of the tracked targets and each of the detected targets according to the position detection information and the position prediction information; for each of the tracked targets, obtaining a motion matching result according to the motion matching degree and the first matching threshold corresponding to the tracked target; and matching the detected targets and the tracked targets according to the motion matching results to obtain a tracking result.
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公开(公告)号：US11232289B2
公开(公告)日：2022-01-25
申请号：US16817554
申请日：2020-03-12
Applicant: UBTECH ROBOTICS CORP LTD
Inventor： Jun Cheng , Kui Guo , Jing Gu , Jianxin Pang , Youjun Xiong
Abstract: The present disclosure provides a face identification method and a terminal device using the same. The method includes: obtaining a to-be-detected image; performing a brightness enhancement process on the to-be-detected image based on a preset second calculation method to generate a to-be-identified face image; obtaining a first channel value of each channel corresponding to each pixel in the to-be-identified face image; performing another brightness enhancement process on the to-be-identified face image based on each first channel value and a preset first calculation method to obtain a target to-be-identified face image; and performing a face identification process on the target to-be-identified face image to obtain an identification result. Through the above-mentioned scheme, an enhanced face identification manner for the images of low brightness is provided.
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公开(公告)号：US20210181747A1
公开(公告)日：2021-06-17
申请号：US17113132
申请日：2020-12-07
Applicant: UBTECH ROBOTICS CORP LTD
Inventor： Shuping Hu , Jun Cheng , Jingtao Zhang , Miaochen Guo , Dong Wang , Jianxin Pang , Youjun Xiong
Abstract: A robot climbing control method is disclosed. A gravity direction vector in a gravity direction in a camera coordinate system of a robot is obtained. A stair edge of stairs in a scene image is obtained and an edge direction vector of the stair edge in the camera coordinate system is determined. A position parameter of the robot relative to the stairs is determined according to the gravity direction vector and the edge direction vector. Poses of the robot are adjusted according to the position parameter to control the robot to climb the stairs.
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