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公开(公告)号:US20180137641A1
公开(公告)日:2018-05-17
申请号:US15567949
申请日:2016-03-04
Applicant: ZTE CORPORATION
Inventor: Wenjie CHEN , Xia JIA , Ming LIU
CPC classification number: G06T7/70 , G06K9/6215 , G06T7/11 , G06T7/20 , G06T2207/20068
Abstract: A target tracking method and device are provided. The method includes: determining a vertical projection integral image and a horizontal projection integral image of a first region in a current frame of image captured; calculating a vertical projection curve and a horizontal projection curve of a target image in the current frame of image by utilizing the vertical projection integral image and the horizontal projection integral image of the first region; calculating a similarity between the target image in the current frame of image and the target image in a previous frame of image according to the vertical projection curve and the horizontal projection curve; and determining whether the target image in the current frame of image is a target image to be tracked according to the similarity.
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公开(公告)号:US20170309040A1
公开(公告)日:2017-10-26
申请号:US15500307
申请日:2015-01-23
Applicant: ZTE CORPORATION
Inventor: Ping LU , Jian SUN , Xia JIA , Lizuo JIN , Wenjing WU
CPC classification number: G06T7/73 , G06K9/00281 , G06T11/60 , G06T2207/30201
Abstract: A method and device for positioning human eyes are disclosed. The method includes: acquiring an input image; performing grayscale processing to the image to extract a grayscale feature; extracting a candidate human eye area in the image by employing a center-periphery contrast filter algorithm according to the grayscale feature; extracting left and right eye candidate areas respectively from the candidate human eye area through a pre-created human eye statistical model; and checking pairing on the left and right eye candidate areas to determine positions of left and right eyes.
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公开(公告)号:US20240221426A1
公开(公告)日:2024-07-04
申请号:US18287617
申请日:2022-04-24
Applicant: ZTE CORPORATION
Inventor: Qian XU , Xia JIA , Ming LIU , Yufeng ZHANG , Weiyao LIN
Abstract: The present disclosure provides a behavior detection method, including: acquiring data of a plurality of video image frames from a video stream; and detecting a pedestrian behavior in the video stream according to the data of the plurality of video image frames, the detecting a pedestrian behavior in the video stream according to the data of the plurality of video image frames includes at least: inputting the data of the plurality of video image frames into a two-dimensional convolutional neural network, and identifying the pedestrian behavior in the video stream according to an association relationship between time sequences of the data of the plurality of video image frames and the data of the plurality of video image frames. The present disclosure further provides an electronic device, and a computer-readable storage medium.
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