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公开(公告)号:US20210042548A1
公开(公告)日:2021-02-11
申请号:US17073035
申请日:2020-10-16
发明人: Wenhan Luo , Yaodong Wang , Wei Liu
摘要: Exemplary embodiments of this disclosure provide a living body detection method and apparatus, an electronic device, a storage medium, and a payment system, a video surveillance system, and an access system to which the living body detection method is applied, and generally belong to the field of biometric recognition technologies. The living body detection method can include obtaining an image of a to-be-detected object performing key point detection on a biometric feature corresponding to the to-be-detected object in the image, and constructing a constraint box in the image according to detected key points. Further, the method can include capturing a shape change of the constraint box constructed in the image, and determining the to-be-detected object as a prosthesis in response to capturing an abnormal deformation of the constraint box or detecting no key points.
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公开(公告)号:US11721087B2
公开(公告)日:2023-08-08
申请号:US17070435
申请日:2020-10-14
发明人: Wenhan Luo , Yaodong Wang , Wei Liu
CPC分类号: G06V10/764 , G06V10/82 , G06V20/52 , G06V40/165 , G06V40/168 , G06V40/172 , G06V40/193 , G06V40/40
摘要: Embodiments of this application provide a living body detection method that can include traversing a plurality of images of a to-be-detected object, and using a currently traversed image as a current image, performing face feature extraction on the current image to obtain an eigenvector corresponding to the current image, the eigenvector describing a structure of a face feature of the object in the current image. The method can further include capturing an action behavior of the to-be-detected object according to a change of the eigenvector corresponding to the current image relative to an eigenvector corresponding to a historical image in a feature sequence, the historical image being a traversed image in the plurality of images, and the feature sequence including an eigenvector corresponding to at least one historical image, and determining the to-be-detected object as a living body in response to capturing the action behavior of the object.
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公开(公告)号:US11688043B2
公开(公告)日:2023-06-27
申请号:US16993922
申请日:2020-08-14
发明人: Kaihao Zhang , Wenhan Luo , Lin Ma , Wei Liu
CPC分类号: G06T5/003 , G06N3/045 , G06N3/08 , G06T5/50 , G06V10/454 , G06T2207/20081 , G06T2207/20084 , G06T2207/20221
摘要: A method of video deblurring by an electronic device is described. The processing circuitry of the electronic device acquires N continuous image frames from a video clip the N being a positive integer, and the N continuous image frames including a blurry image frame to be processed. The processing circuitry of the electronic device performs three-dimensional (3D) convolution processing on the N continuous image frames with a generative adversarial network model, to acquire spatio-temporal information corresponding to the blurry image frame. The spatio-temporal information includes spatial feature information of the blurry image frame, and temporal feature information between the blurry image frame and a neighboring image frame of the N continuous image frames The processing circuitry of the electronic device performs deblurring processing on the blurry image frame by using the spatio-temporal information corresponding to the blurry image frame through the generative adversarial network model, to output a sharp image frame.
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公开(公告)号:US11610082B2
公开(公告)日:2023-03-21
申请号:US17187473
申请日:2021-02-26
发明人: Haozhi Huang , Hao Wang , Wenhan Luo , Lin Ma , Peng Yang , Wenhao Jiang , Xiaolong Zhu , Wei Liu
IPC分类号: G06V10/00 , G06K9/62 , G06N3/04 , G06N3/08 , G06K9/00 , G06V10/30 , G06V10/44 , G06V10/75 , G06V10/98 , G06V20/40 , G06T5/00
摘要: A method, apparatus, and storage medium for training a neural network model used for image processing are described. The method includes: obtaining a plurality of video frames; inputting the plurality of video frames through a neural network model so that the neural network model outputs intermediate images; obtaining optical flow information between an early video frame and a later video frame; modifying an intermediate image corresponding to the early video frame according to the optical flow information to obtain an expected-intermediate image; determining a time loss between an intermediate image corresponding to the later video frame and the expected-intermediate image; determining a feature loss between the intermediate images and a target feature image; and training the neural network model according to the time loss and the feature loss, and returning to obtaining a plurality of video frames continue training until the neural network model satisfies a training finishing condition.
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公开(公告)号:US12008810B2
公开(公告)日:2024-06-11
申请号:US17225969
申请日:2021-04-08
发明人: Zhenfang Chen , Lin Ma , Wenhan Luo , Wei Liu
IPC分类号: G06V20/40 , G06F18/214 , G06F40/279 , G06N3/08 , G06V10/22 , G06V10/44 , G06V10/75 , G06V10/764 , G06V10/82
CPC分类号: G06V20/46 , G06F18/2148 , G06F40/279 , G06N3/08 , G06V10/22 , G06V10/454 , G06V10/758 , G06V10/764 , G06V10/82
摘要: This application discloses a video sequence selection method, applicable to a computer device, the method including: receiving a to-be-matched video and a to-be-matched text, the to-be-matched text having a to-be-matched text feature sequence; invoking a spatiotemporal candidate region generator to extract a spatiotemporal candidate region set from the to-be-matched video, the spatiotemporal candidate region set including N spatiotemporal candidate regions; performing feature extraction on each spatiotemporal candidate region by using a convolutional neural network, to obtain N to-be-matched video feature sequences; invoking an attention-based interactor to obtain a matching score corresponding to each spatiotemporal candidate region, the matching score being used for representing a matching relationship between the spatiotemporal candidate region and the to-be-matched text; and selecting a target spatiotemporal candidate region from the spatiotemporal candidate region set according to the matching score corresponding to each spatiotemporal candidate region, and outputting the target spatiotemporal candidate region. In this application, an association between the video and the text in time sequence is considered during matching, thereby increasing a degree of matching between a video sequence and the text.
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公开(公告)号:US12001959B2
公开(公告)日:2024-06-04
申请号:US17864730
申请日:2022-07-14
发明人: Wenhan Luo , Lin Ma , Wei Liu
IPC分类号: G06N3/088 , G06F18/21 , G06F18/214 , G06N3/045 , G06N3/047 , G06N3/08 , G06T15/20 , G06V20/40
CPC分类号: G06N3/088 , G06F18/214 , G06F18/2193 , G06N3/045 , G06V20/41 , G06V20/49
摘要: The present disclosure describes methods, devices, and storage medium for generating a time-lapse photography video with a neural network model. The method includes obtaining a training sample. The training sample includes a training video and an image set. The method includes obtaining through training according to the training sample, a neural network model to satisfy a training ending condition, the neural network model comprising a basic network and an optimization network, by using the image set as an input to the basic network, the basic network being a first generative adversarial network for performing content modeling, generating a basic time-lapse photography video as an output of the basic network, using the basic time-lapse photography video as an input to the optimization network, the optimization network being a second generative adversarial network for performing motion state modeling, and generating an optimized time-lapse photography video as an output of the optimization network.
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公开(公告)号:US20230343070A1
公开(公告)日:2023-10-26
申请号:US18333357
申请日:2023-06-12
发明人: Wenhan Luo , Yaodong Wang , Wei Liu
CPC分类号: G06V10/764 , G06V40/168 , G06V40/172 , G06V10/82 , G06V20/52 , G06V40/165 , G06V40/193 , G06V40/40
摘要: An access system, including a reception device, a recognition server, and an access control device. The reception device acquires a plurality of images of an access object. The recognition server includes a liveness detection apparatus determines corresponding eigenvectors according to the plurality of images of the access object, captures an action behavior of the access object according to a relative change between the determined eigenvectors, and determines the access object as a live body in response to capturing the action behavior of the access object. The recognition server performs identity recognition on the access object when the access object is the live body so that the access control device configures an access permission for the access object that completes the identity recognition successfully, and the access object controls, according to the configured access permission, an access barrier of a specified work region to perform a release action.
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公开(公告)号:US11551481B2
公开(公告)日:2023-01-10
申请号:US17073035
申请日:2020-10-16
发明人: Wenhan Luo , Yaodong Wang , Wei Liu
IPC分类号: G06T7/292 , G06V40/40 , G07C9/37 , G07C9/10 , G06F21/32 , G06Q20/18 , G06Q20/40 , H04N7/18 , G06V20/52 , G06V40/20 , G06V40/16
摘要: Exemplary embodiments of this disclosure provide a living body detection method and apparatus, an electronic device, a storage medium, and a payment system, a video surveillance system, and an access system to which the living body detection method is applied, and generally belong to the field of biometric recognition technologies. The living body detection method can include obtaining an image of a to-be-detected object performing key point detection on a biometric feature corresponding to the to-be-detected object in the image, and constructing a constraint box in the image according to detected key points. Further, the method can include capturing a shape change of the constraint box constructed in the image, and determining the to-be-detected object as a prosthesis in response to capturing an abnormal deformation of the constraint box or detecting no key points.
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公开(公告)号:US11429817B2
公开(公告)日:2022-08-30
申请号:US16892587
申请日:2020-06-04
发明人: Wenhan Luo , Lin Ma , Wei Liu
摘要: The present disclosure describes methods, devices, and storage medium for generating a time-lapse photography video with a neural network model. The method includes obtaining a training sample. The training sample includes a training video and an image set. The method includes obtaining through training according to the training sample, a neural network model to satisfy a training ending condition, the neural network model comprising a basic network and an optimization network, by using the image set as an input to the basic network, the basic network being a first generative adversarial network for performing content modeling, generating a basic time-lapse photography video as an output of the basic network, using the basic time-lapse photography video as an input to the optimization network, the optimization network being a second generative adversarial network for performing motion state modeling, and generating an optimized time-lapse photography video as an output of the optimization network.
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公开(公告)号:US11145069B2
公开(公告)日:2021-10-12
申请号:US16538310
申请日:2019-08-12
发明人: Wenhan Luo
摘要: Aspects of the disclosure provide an apparatus for target tracking including processing circuitry that obtains a plurality of target instances according to a target detection on image data. Each of the plurality of target instances corresponds to one of a plurality of tracked targets. The processing circuitry determines a plurality of trajectory segments, each of which indicates a trajectory of a subset of the target instances corresponding to a same tracked target. The processing circuitry determines feature information of the plurality of trajectory segments. The processing circuitry performs clustering on specified trajectory segments of the plurality of trajectory segments according to the feature information of the specified trajectory segments, to obtain a type distribution of the specified trajectory segments. The processing circuitry determines, according to the type distribution of the specified trajectory segments, a target tracking result including a same type of the specified trajectory segments.
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