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    • 3. 发明授权
    • Video-teleconferencing system with eye-gaze correction
    • 具有眼睛注视校正的视频会议系统
    • US06771303B2
    • 2004-08-03
    • US10128888
    • 2002-04-23
    • Zhengyou ZhangRuigang Yang
    • Zhengyou ZhangRuigang Yang
    • H04N714
    • H04N7/144
    • Correcting for eye-gaze in video communication devices is accomplished by blending information captured from a stereoscopic view of the conferee and generating a virtual image of the conferee. A personalized face model of the conferee is captured to track head position of the conferee. First and second video images representative of a first conferee taken from different views are concurrently captured. A head position of the first conferee is tracked from the first and second video images. Matching features and contours from the first and second video images are ascertained. The head position as well as the matching features and contours from the first and second video images are synthesized to generate a virtual image video stream of the first conferee that makes the first conferee appear to be making eye contact with a second conferee who is watching the virtual image video stream.
    • 在视频通信设备中校正眼睛注视是通过混合从与会者的立体视图获取的信息并产生与会者的虚拟图像来实现的。 捕获与会者的个性化面部模型,以跟踪与会者的头部位置。 同时捕获代表从不同视图取得的第一同伴的第一和第二视频图像。 从第一和第二视频图像追踪第一个与会者的头部位置。 确定来自第一和第二视频图像的匹配特征和轮廓。 头部位置以及来自第一和第二视频图像的匹配特征和轮廓被合成以产生第一与会者的虚拟图像视频流,使得第一与会者看起来正在与正在观看的第二参与者进行目标接触 虚拟图像视频流。
    • 4. 发明授权
    • Head pose tracking system
    • 头姿态跟踪系统
    • US07515173B2
    • 2009-04-07
    • US10154892
    • 2002-05-23
    • Zhengyou ZhangRuigang Yang
    • Zhengyou ZhangRuigang Yang
    • H04N7/14
    • H04N7/15H04N7/144
    • Video images representative of a conferee's head are received and evaluated with respect to a reference model to monitor a head position of the conferee. A personalized face model of the conferee is captured to track head position of the conferee. In a stereo implementation, first and second video images representative of a first conferee taken from different views are concurrently captured. A head position of the first conferee is tracked from the first and second video images. The tracking of head-position through a personalized model-based approach can be used in a number of applications such as human-computer interaction and eye-gaze correction for video conferencing.
    • 代表参加者头部的视频图像被接收并且相对于参考模型进行评估以监视与会者的头部位置。 捕获与会者的个性化面部模型,以跟踪与会者的头部位置。 在立体声实现中,同时捕获代表从不同视图拍摄的第一与会者的第一和第二视频图像。 从第一和第二视频图像追踪第一个与会者的头部位置。 通过基于个性化的基于模型的方法跟踪头位可以用于许多应用,例如用于视频会议的人机交互和眼睛注视校正。
    • 5. 发明授权
    • Depth-aware blur kernel estimation method for iris deblurring
    • 用于虹膜脱模的深度感知模糊核估计方法
    • US09313460B2
    • 2016-04-12
    • US13525511
    • 2012-06-18
    • Liu RenXinyu HuangRuigang Yang
    • Liu RenXinyu HuangRuigang Yang
    • G06K9/00H04N7/18G06T5/00
    • H04N7/18G06K9/00604G06T5/003G06T2207/10016G06T2207/10028G06T2207/10048G06T2207/30201
    • Estimating a blur kernel distribution for visual iris recognition includes determining a first mathematical relationship between an in-focus position of a camera lens and a distance between the lens and an iris whose image is to be captured by the lens. A second mathematical relationship between the in-focus position of the lens and a standard deviation defining a Gaussian blur kernel distribution is estimated. The first mathematical relationship is used to ascertain a desired focus position of the lens based upon the actual position of the living being's eye at the point in time. The second mathematical relationship is used to calculate a standard deviation defining a Gaussian blur kernel distribution. The produced image is digitally unblurred by using the blur kernel distribution defined by the calculated standard deviation.
    • 估计用于视觉虹膜识别的模糊核心分布包括确定相机透镜的对焦位置与透镜与其图像将被透镜捕获的虹膜之间的距离之间的第一数学关系。 估计透镜的聚焦位置与限定高斯模糊核分布的标准偏差之间的第二数学关系。 第一数学关系用于基于在该时刻的生命的眼睛的实际位置来确定镜片的期望的焦点位置。 第二个数学关系用于计算定义高斯模糊核分布的标准偏差。 通过使用由计算出的标准偏差定义的模糊核心分布,产生的图像被数字化。
    • 8. 发明申请
    • DEPTH-AWARE BLUR KERNEL ESTIMATION METHOD FOR IRIS DEBLURRING
    • 深度识别盲点估计方法
    • US20130147937A1
    • 2013-06-13
    • US13525511
    • 2012-06-18
    • Liu RenXinyu HuangRuigang Yang
    • Liu RenXinyu HuangRuigang Yang
    • H04N7/18
    • H04N7/18G06K9/00604G06T5/003G06T2207/10016G06T2207/10028G06T2207/10048G06T2207/30201
    • Estimating a blur kernel distribution for visual iris recognition includes determining a first mathematical relationship between an in-focus position of a camera lens and a distance between the lens and an iris whose image is to be captured by the lens. A second mathematical relationship between the in-focus position of the lens and a standard deviation defining a Gaussian blur kernel distribution is estimated. The first mathematical relationship is used to ascertain a desired focus position of the lens based upon the actual position of the living being's eye at the point in time. The second mathematical relationship is used to calculate a standard deviation defining a Gaussian blur kernel distribution. The produced image is digitally unblurred by using the blur kernel distribution defined by the calculated standard deviation.
    • 估计用于视觉虹膜识别的模糊核心分布包括确定相机透镜的对焦位置与透镜与其图像将被透镜捕获的虹膜之间的距离之间的第一数学关系。 估计透镜的聚焦位置与限定高斯模糊核分布的标准偏差之间的第二数学关系。 第一数学关系用于基于在该时刻的生命的眼睛的实际位置来确定镜片的期望的焦点位置。 第二个数学关系用于计算定义高斯模糊核分布的标准偏差。 通过使用由计算出的标准偏差定义的模糊核心分布,产生的图像被数字化。
    • 9. 发明授权
    • Depth-aware blur kernel estimation method for iris deblurring
    • 用于虹膜脱模的深度感知模糊核估计方法
    • US08203602B2
    • 2012-06-19
    • US12367069
    • 2009-02-06
    • Liu RenXinyu HuangRuigang Yang
    • Liu RenXinyu HuangRuigang Yang
    • G06K9/00
    • H04N7/18G06K9/00604G06T5/003G06T2207/10016G06T2207/10028G06T2207/10048G06T2207/30201
    • A method of estimating a blur kernel distribution for visual iris recognition includes determining a first mathematical relationship between an in-focus position of a camera lens and a distance between the lens and an iris whose image is to be captured by the lens. The first relationship is used to estimate a second mathematical relationship between the in-focus position of the lens and a standard deviation defining a Gaussian blur kernel distribution. A position of an eye of a living being at a future point in time is predicted. A focus position of the camera lens is adjusted based upon the predicted position of the eye. The camera lens with the adjusted focus position is used to produce an image of the living being's eye at the point in time. An actual position of the living being's eye at the point in time is sensed. The first relationship is used to ascertain a desired focus position of the lens based upon the actual position of the living being's eye at the point in time. The second relationship is used to calculate a standard deviation defining a Gaussian blur kernel distribution. The calculating is based upon a difference between the adjusted focus position and the desired focus position of the lens.
    • 估计用于视觉虹膜识别的模糊核分布的方法包括确定相机透镜的对焦位置与透镜与其图像将由透镜捕获的光圈之间的距离之间的第一数学关系。 第一关系用于估计透镜的聚焦位置与定义高斯模糊核分布的标准偏差之间的第二数学关系。 预测未来时期生活的眼睛的位置。 基于预测的眼睛位置来调整照相机镜头的对焦位置。 具有调整对焦位置的相机镜头用于在时间点上产生生命眼睛的图像。 感觉到生活在眼前的实际位置。 第一关系用于基于在该时间点的生命的眼睛的实际位置来确定镜片的期望的焦点位置。 第二个关系用于计算定义高斯模糊核分布的标准偏差。 该计算基于调整后的焦点位置与镜片的期望对焦位置之间的差异。