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1.发明授权公开(公告)号：US11995863B2
公开(公告)日：2024-05-28
申请号：US17416590
申请日：2020-09-29
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Yu Gu , Jinglin Yang
CPC classification number: G06T7/73 , G06T7/80 , G06V10/22 , G06T2207/30196 , G06T2207/30242
Abstract: Disclosed are a method for counting regional population, a computer device and a computer readable storage medium. The method for counting regional population includes: acquiring an image to be analyzed in a target region; detecting a position of each first human body part in the image to be analyzed; determining, according to the position of each first human body part in the image to be analyzed and a first transformation relation, a physical position of each first human body part in the target region; and determining the population in each sub-region according to a relative positional relation between the position of the first human body part in the image to be analyzed and the sub-image, as well as a relative positional relation between the physical position of the first human body part and the sub-region.
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公开(公告)号：US12056897B2
公开(公告)日：2024-08-06
申请号：US17765366
申请日：2021-04-09
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Jinglin Yang
CPC classification number: G06T7/77 , G06T7/75 , G06T2207/10004 , G06T2207/20076 , G06T2207/20081
Abstract: A target detection method includes: determining detection points corresponding to regions in an image to be detected and a probability value of a target in a region corresponding to each detection point according to the image to be detected; screening out a first detection point having a maximum probability value, and second detection point(s) having probability value(s) less than the probability value of the first detection point and greater than or equal to a probability threshold; if a first distance between each second detection point and the first detection point is greater than or equal to a distance threshold, updating an original probability value of the second detection point to obtain an updated probability value; comparing the updated probability value with the probability threshold to obtain a comparison result; and determining whether a new target in a region corresponding to the second detection point according to the comparison result.
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公开(公告)号：US11756224B2
公开(公告)日：2023-09-12
申请号：US16966611
申请日：2019-06-27
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Jinglin Yang
Abstract: The invention discloses an image detection method, apparatus, device and a medium. The method includes: determining one or more edge points in an input image and gradient directions thereof; generating an initial matrix with the same size as the input image, and assigning the same initial value to all matrix elements in the initial matrix; for each pixel point located in an accumulation region of each edge point, assigning a corresponding accumulation value to a matrix element in the initial matrix corresponding to the pixel point, to obtain an accumulation matrix; determining one or more circle-center positions in the input image based on the accumulation matrix; wherein, the accumulation region of each edge point includes a first direction line for accumulation along the gradient direction of the edge point and a second direction line for accumulation along the direction opposite to the gradient direction of the edge point.
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公开(公告)号：US10896354B2
公开(公告)日：2021-01-19
申请号：US16141637
申请日：2018-09-25
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Jinglin Yang
Abstract: The present disclosure relates to a target detection method and device, a computing device and a readable storage medium. The target detection method include performing target detection using a convolutional neural network comprising a plurality of convolutional layers. The method include performing a branch convolutional process on at least one of the convolutional layers to obtain a branch detection result. The method includes performing a fusion process on the branch detection result, or on the branch detection result and a detection result of a last convolutional layer in the convolutional neural network, and transmitting a result of the fusion process to a fully connected layer.
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公开(公告)号：US10803554B2
公开(公告)日：2020-10-13
申请号：US16247202
申请日：2019-01-14
Applicant: BOE Technology Group Co., Ltd.
Inventor： Jinglin Yang
Abstract: An image processing method and an image processing device are provided. The method includes acquiring an initial image, performing super-pixel segmentation on the initial image, and acquiring final image blocks; extracting a region of interest from the final image blocks in accordance with an image feature of a target image; and performing super-resolution reconstruction on the region of interest and acquiring an optimized image.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20210158699A1
公开(公告)日：2021-05-27
申请号：US16609729
申请日：2019-01-22
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Jinglin Yang
Abstract: The present disclosure relates to a method, device, computer readable media, and electronic devices for identifying a traffic light signal from an image. The method for identifying a traffic light signal from an image includes extracting, based on a deep neural network, multiple layers of first feature maps corresponding to different layers of the deep neural network from the image. The method includes selecting at least two layers of the first feature maps having different scales from the multiple layers of the first feature maps. The method includes inputting the at least two layers of the first feature maps to a convolution layer having a convolution kernel matching a shape of a traffic light to obtain a second feature map. The method includes obtaining a detection result of the traffic light signal based on the second feature map.
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公开(公告)号：US10592761B2
公开(公告)日：2020-03-17
申请号：US15915954
申请日：2018-03-08
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Jinglin Yang
Abstract: The present disclosure discloses an image processing method and device. The image processing method includes: dividing a detection image into a plurality of first subregions, dividing a template image into a plurality of second subregions, calculating a principal rotation direction of each first subregion with respect to the corresponding second subregion; and calculating a principal rotation direction of the detection image according to the principal rotation directions of the plurality of first subregions.
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公开(公告)号：US20190303731A1
公开(公告)日：2019-10-03
申请号：US16141637
申请日：2018-09-25
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Jinglin Yang
Abstract: The present disclosure relates to a target detection method and device, a computing device and a readable storage medium. The target detection method include performing target detection using a convolutional neural network comprising a plurality of convolutional layers. The method include performing a branch convolutional process on at least one of the convolutional layers to obtain a branch detection result. The method includes performing a fusion process on the branch detection result, or on the branch detection result and a detection result of a last convolutional layer in the convolutional neural network, and transmitting a result of the fusion process to a fully connected layer.
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公开(公告)号：US11830273B2
公开(公告)日：2023-11-28
申请号：US17280821
申请日：2020-07-28
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Jinglin Yang
CPC classification number: G06V40/10 , G06F18/22 , G06V10/25 , G06V20/46 , G06V2201/07
Abstract: A multi-target pedestrian tracking method, a multi-target pedestrian tracking apparatus and a multi-target pedestrian tracking device are provided, related to the field of image processing technologies. The multi-target pedestrian tracking method includes: detecting a plurality of candidate pedestrian detection boxes in a current frame of image to be detected, where a temporary tracking identification and a tracking counter are set for each of the plurality of candidate pedestrian detection boxes; and determining whether each of the plurality of candidate pedestrian detection boxes matches an existing tracking box, updating a value of the tracking counter according to a determination result, and continuing to detect a next frame of image to be detected. When the value of the tracking counter reaches a first preset threshold, the updating the value of the tracking counter is stopped, and the temporary tracking identification is converted to a confirmed tracking identification.
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10.发明授权公开(公告)号：US11410549B2
公开(公告)日：2022-08-09
申请号：US16609729
申请日：2019-01-22
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Jinglin Yang
Abstract: The present disclosure relates to a method, device, computer readable media, and electronic devices for identifying a traffic light signal from an image. The method for identifying a traffic light signal from an image includes extracting, based on a deep neural network, multiple layers of first feature maps corresponding to different layers of the deep neural network from the image. The method includes selecting at least two layers of the first feature maps having different scales from the multiple layers of the first feature maps. The method includes inputting the at least two layers of the first feature maps to a convolution layer having a convolution kernel matching a shape of a traffic light to obtain a second feature map. The method includes obtaining a detection result of the traffic light signal based on the second feature map.
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