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公开(公告)号：US20180374219A1
公开(公告)日：2018-12-27
申请号：US15909402
申请日：2018-03-01
Applicant: Shanghai Xiaoi Robot Technology Co., Ltd.
Inventor： Bo ZHANG , Pinpin ZHU
CPC classification number: G06T7/246 , G06K9/00228 , G06K9/00268 , G06K9/00295 , G06K9/6217 , G06K9/6228 , G06K2009/3291 , G06T2207/10016 , G06T2207/30201
Abstract: A video tracking method comprises: determining a first tracking target in a video, and performing a video tracking process on the first tracking target based on the video; performing area overlap degree calculation on the first tracking target in a current image and the first tracking target in a past image during the video tracking process, the past image being an image obtained when the first tracking target was tracked last time in the video tracking process; extracting respective feature information of feature points of the first tracking target in the video during the video tracking process on the first tracking target; matching the extracted respective feature information of the feature points of the first tracking target in the current image with the respective feature information of corresponding feature points of the first tracking target in the past image if a result of the area overlap degree calculation is less than or equal to a preset threshold; and continuing the video tracking process on the first tracking target if the respective feature information of at least a preset number of feature points among the extracted feature points in the current image matches with the feature information of corresponding feature points of the first tracking target in the past image.
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公开(公告)号：US20200273179A1
公开(公告)日：2020-08-27
申请号：US16871996
申请日：2020-05-11
Applicant: Shanghai Xiaoi Robot Technology Co., Ltd.
Inventor： Bo ZHANG , Pinpin ZHU
Abstract: An object recognition device includes a memory, a processor and a computer program stored in the memory and executed by the processor. When the computer program is executed by the processor, the processor implements the following steps: extracting object recognition feature vectors based on at least one frame image of the video on the first tracking target; matching the extracted object recognition feature vectors with object feature vectors of registered objects in a registration object library, the registration object library being established based on pre-learning of the object feature vectors in images of the registered objects; and taking one of the registered objects as a recognition result if the extracted object recognition feature vectors match with the object feature vectors of the one of the registered objects.
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