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1. 发明授权

US08498454B2 Optimal subspaces for face recognition 有权
标题翻译：面部识别的最佳子空间
公开(公告)号：US08498454B2
公开(公告)日：2013-07-30
申请号：US12627039
申请日：2009-11-30
申请人： Jilin Tu , Frederick Wilson Wheeler , Peter Henry Tu , Xiaoming Liu , Yan Tong
发明人： Jilin Tu , Frederick Wilson Wheeler , Peter Henry Tu , Xiaoming Liu , Yan Tong
IPC分类号： G06K9/00
CPC分类号： G06K9/6234 , G06K9/00288 , G06K9/6215
摘要： A technique for optimizing object recognition is disclosed. The technique includes receiving at least one image of an object and at least one reference image. The technique further includes identifying at least one performance metric corresponding to an object recognition task. The identified performance metric is optimized to generate the corresponding optimized performance metric by determining an optimal subspace based on a determined objective function corresponding to the object recognition task and a difference between the received image and the corresponding reference image. Subsequently, the technique includes comparing the received image with the reference image based on the optimized performance metric for performing the object recognition task.
摘要翻译：公开了一种用于优化对象识别的技术。该技术包括接收对象和至少一个参考图像的至少一个图像。该技术还包括识别对应于对象识别任务的至少一个性能量度。通过基于与对象识别任务相对应的确定的目标函数和接收到的图像与对应的参考图像之间的差异来确定最佳子空间来优化识别的性能度量以产生相应的优化性能度量。随后，该技术包括基于用于执行对象识别任务的优化性能度量来比较接收到的图像与参考图像。

2. 发明申请

US20110013845A1 OPTIMAL SUBSPACES FOR FACE RECOGNITION 有权
标题翻译：面向认可的最佳选择
公开(公告)号：US20110013845A1
公开(公告)日：2011-01-20
申请号：US12627039
申请日：2009-11-30
申请人： Jilin Tu , Frederick Wilson Wheeler , Peter Henry Tu , Xiaoming Liu , Yan Tong
发明人： Jilin Tu , Frederick Wilson Wheeler , Peter Henry Tu , Xiaoming Liu , Yan Tong
IPC分类号： G06K9/68
CPC分类号： G06K9/6234 , G06K9/00288 , G06K9/6215
摘要： A technique for optimizing object recognition is disclosed. The technique includes receiving at least one image of an object and at least one reference image. The technique further includes identifying at least one performance metric corresponding to an object recognition task. The identified performance metric is optimized to generate the corresponding optimized performance metric by determining an optimal subspace based on a determined objective function corresponding to the object recognition task and a difference between the received image and the corresponding reference image. Subsequently, the technique includes comparing the received image with the reference image based on the optimized performance metric for performing the object recognition task.
摘要翻译：公开了一种用于优化对象识别的技术。该技术包括接收对象和至少一个参考图像的至少一个图像。该技术还包括识别对应于对象识别任务的至少一个性能量度。通过基于与对象识别任务相对应的确定的目标函数和接收到的图像与对应的参考图像之间的差异来确定最佳子空间来优化识别的性能度量以产生相应的优化性能度量。随后，该技术包括基于用于执行对象识别任务的优化性能度量来比较接收到的图像与参考图像。

3. 发明申请

US20100246980A1 SYSTEM AND METHOD FOR AUTOMATIC LANDMARK LABELING WITH MINIMAL SUPERVISION 有权
标题翻译：自动地标标签系统与方法与最小监控
公开(公告)号：US20100246980A1
公开(公告)日：2010-09-30
申请号：US12533066
申请日：2009-07-31
申请人： Yan Tong , Xiaoming Liu , Jilin Tu , Peter Henry Tu , Frederick Wilson Wheeler
发明人： Yan Tong , Xiaoming Liu , Jilin Tu , Peter Henry Tu , Frederick Wilson Wheeler
IPC分类号： G06K9/62 , G06K9/00
CPC分类号： G06K9/66 , G06K9/00228 , G06T7/33 , G06T7/35 , G06T2207/20121 , G06T2207/30201
摘要： A system and method for estimating a set of landmarks for a large image ensemble employs only a small number of manually labeled images from the ensemble and avoids labor-intensive and error-prone object detection, tracking and alignment learning task limitations associated with manual image labeling techniques. A semi-supervised least squares congealing approach is employed to minimize an objective function defined on both labeled and unlabeled images. A shape model is learned on-line to constrain the landmark configuration. A partitioning strategy allows coarse-to-fine landmark estimation.
摘要翻译：用于估计大图像集合的一组地标的系统和方法仅使用来自集合的少量手动标记的图像，并且避免与手动图像标签相关联的劳动密集型和易出错的对象检测，跟踪和对准学习任务限制技术采用半监督的最小二乘法凝结方法来最小化在标记和未标记图像上定义的目标函数。形状模型在线学习以约束地标配置。分区策略允许粗略到精细的地标估计。

4. 发明授权

US08442330B2 System and method for automatic landmark labeling with minimal supervision 有权
标题翻译：最小监督的自动地标标签系统和方法
公开(公告)号：US08442330B2
公开(公告)日：2013-05-14
申请号：US12533066
申请日：2009-07-31
申请人： Yan Tong , Xiaoming Liu , Jilin Tu , Peter Henry Tu , Frederick Wilson Wheeler
发明人： Yan Tong , Xiaoming Liu , Jilin Tu , Peter Henry Tu , Frederick Wilson Wheeler
IPC分类号： G06K9/62 , G06K9/74
CPC分类号： G06K9/66 , G06K9/00228 , G06T7/33 , G06T7/35 , G06T2207/20121 , G06T2207/30201
摘要： A system and method for estimating a set of landmarks for a large image ensemble employs only a small number of manually labeled images from the ensemble and avoids labor-intensive and error-prone object detection, tracking and alignment learning task limitations associated with manual image labeling techniques. A semi-supervised least squares congealing approach is employed to minimize an objective function defined on both labeled and unlabeled images. A shape model is learned on-line to constrain the landmark configuration. A partitioning strategy allows coarse-to-fine landmark estimation.
摘要翻译：用于估计大图像集合的一组地标的系统和方法仅使用来自集合的少量手动标记的图像，并且避免与手动图像标签相关联的劳动密集型和易出错的对象检测，跟踪和对准学习任务限制技术采用半监督的最小二乘法凝结方法来最小化在标记和未标记图像上定义的目标函数。形状模型在线学习以约束地标配置。分区策略允许粗略到精细的地标估计。

5. 发明申请

US20120237117A1 OPTIMAL GRADIENT PURSUIT FOR IMAGE ALIGNMENT 有权
标题翻译：用于图像对齐的最佳梯度图像
公开(公告)号：US20120237117A1
公开(公告)日：2012-09-20
申请号：US13052097
申请日：2011-03-20
申请人： Xiaoming Liu , Frederick Wilson Wheeler , Peter Henry Tu , Jilin Tu
发明人： Xiaoming Liu , Frederick Wilson Wheeler , Peter Henry Tu , Jilin Tu
IPC分类号： G06K9/46 , G06K9/48 , G06K9/62
CPC分类号： G06K9/3241 , G06K9/00228
摘要： A method for image alignment is disclosed. In one embodiment, the method includes acquiring a facial image of a person and using a discriminative face alignment model to fit a generic facial mesh to the facial image to facilitate locating of facial features. The discriminative face alignment model may include a generative shape model component and a discriminative appearance model component. Further, the discriminative appearance model component may have been trained to estimate a score function that minimizes the angle between a gradient direction and a vector pointing toward a ground-truth shape parameter. Additional methods, systems, and articles of manufacture are also disclosed.
摘要翻译：公开了一种用于图像对准的方法。在一个实施例中，该方法包括获取人的面部图像并使用区别性面部对准模型来将面部图像拟合为面部图像，以便于面部特征的定位。鉴别面部对齐模型可以包括生成形状模型组件和鉴别外观模型组件。此外，鉴别外观模型组件可能已经被训练以估计最小化梯度方向和指向地面真实形状参数的向量之间的角度的得分函数。还公开了附加的方法，系统和制品。

6. 发明授权

US08478077B2 Optimal gradient pursuit for image alignment 有权
标题翻译：图像对齐的最佳梯度追踪
公开(公告)号：US08478077B2
公开(公告)日：2013-07-02
申请号：US13052097
申请日：2011-03-20
申请人： Xiaoming Liu , Frederick Wilson Wheeler , Peter Henry Tu , Jilin Tu
发明人： Xiaoming Liu , Frederick Wilson Wheeler , Peter Henry Tu , Jilin Tu
IPC分类号： G06K9/32 , G06K9/62 , G06K9/66 , G06K9/36 , G06K9/48
CPC分类号： G06K9/3241 , G06K9/00228
摘要： A method for image alignment is disclosed. In one embodiment, the method includes acquiring a facial image of a person and using a discriminative face alignment model to fit a generic facial mesh to the facial image to facilitate locating of facial features. The discriminative face alignment model may include a generative shape model component and a discriminative appearance model component. Further, the discriminative appearance model component may have been trained to estimate a score function that minimizes the angle between a gradient direction and a vector pointing toward a ground-truth shape parameter. Additional methods, systems, and articles of manufacture are also disclosed.
摘要翻译：公开了一种用于图像对准的方法。在一个实施例中，该方法包括获取人的面部图像并使用区别性面部对准模型来将面部图像拟合为面部图像，以便于面部特征的定位。鉴别面部对齐模型可以包括生成形状模型组件和鉴别外观模型组件。此外，鉴别外观模型组件可能已经被训练以估计最小化梯度方向和指向地面真实形状参数的向量之间的角度的得分函数。还公开了附加的方法，系统和制品。

7. 发明授权

US08155399B2 Generic face alignment via boosting 有权
标题翻译：通过升压进行通用面对齐
公开(公告)号：US08155399B2
公开(公告)日：2012-04-10
申请号：US12056051
申请日：2008-03-26
申请人： Xiaoming Liu , Peter Henry Tu , Frederick Wilson Wheeler
发明人： Xiaoming Liu , Peter Henry Tu , Frederick Wilson Wheeler
IPC分类号： G06K9/62
CPC分类号： G06K9/00241 , G06K9/621
摘要： There is provided a discriminative framework for image alignment. Image alignment is generally the process of moving and deforming a template to minimize the distance between the template and an image. There are essentially three elements to image alignment, namely template representation, distance metric, and optimization method. For template representation, given a face dataset with ground truth landmarks, a boosting-based classifier is trained that is able to learn the decision boundary between two classes—the warped images from ground truth landmarks (e.g., positive class) and those from perturbed landmarks (e.g., negative class). A set of trained weak classifiers based on Haar-like rectangular features determines a boosted appearance model. A distance metric is a score from the strong classifier, and image alignment is the process of optimizing (e.g., maximizing) the classification score. On the generic face alignment problem, the proposed framework greatly improves the robustness, accuracy, and efficiency of alignment.
摘要翻译：提供了一种用于图像对齐的辨别框架。图像对齐通常是移动和变形模板的过程，以最小化模板和图像之间的距离。图像对齐基本上有三个要素，即模板表示，距离度量和优化方法。对于模板表示，给定一个具有地面真实地标的面部数据集，训练有素的分类器能够学习两个类之间的决策边界 - 来自地面真实地标（例如，积极的类）和来自扰动地标的变形图像（例如负面班）。基于哈尔式矩形特征的一组经过训练的弱分类器决定了外观模型的提升。距离度量是来自强分类器的分数，图像对准是优化（例如，最大化）分类分数的过程。在通用面对齐问题上，提出的框架大大提高了对齐的鲁棒性，准确性和效率。

8. 发明申请

US20090257625A1 METHODS INVOLVING FACE MODEL FITTING 有权
标题翻译：涉及面模型的方法
公开(公告)号：US20090257625A1
公开(公告)日：2009-10-15
申请号：US12100620
申请日：2008-04-10
申请人： Xiaoming Liu , Peter Henry Tu , Frederick Wilson Wheeler
发明人： Xiaoming Liu , Peter Henry Tu , Frederick Wilson Wheeler
IPC分类号： G06K9/00
CPC分类号： G06K9/00288 , G06K9/00261 , G06K9/621
摘要： A method for face model fitting comprising, receiving a first observed image, receiving a second observed image, and fitting an active appearance model of a third image to the second observed image and the first observed image with an algorithm that includes a first function of a mean-square-error between a warped image of the second observed image and a synthesis of the active appearance model and a second function of a mean-square-error between the warped image of the second observed image and an appearance data of the first observed image.
摘要翻译：一种用于面部模型拟合的方法，包括：接收第一观察图像，接收第二观察图像，以及使用包括第一观察图像的第一函数的第二观察图像和第一观察图像拟合第三图像的活动外观模型第二观察图像的翘曲图像与活动外观模型的合成之间的均方误差以及第二观察图像的翘曲图像与第一观察图像的外观数据之间的均方误差的第二函数图片。

9. 发明申请

US20080175509A1 SYSTEM AND METHOD FOR RECONSTRUCTING RESTORED FACIAL IMAGES FROM VIDEO 有权
标题翻译：用于从视频重构恢复的面部图像的系统和方法
公开(公告)号：US20080175509A1
公开(公告)日：2008-07-24
申请号：US11836316
申请日：2007-08-09
申请人： Frederick Wilson Wheeler , Xiaoming Liu , Peter Henry Tu
发明人： Frederick Wilson Wheeler , Xiaoming Liu , Peter Henry Tu
IPC分类号： G06K9/40
CPC分类号： G06K9/621 , G06K9/00281 , G06T7/33
摘要： A system and method for performing a facial image restoration is described. The system includes an active appearance model component for fitting an active appearance model to a facial image found in each of a plurality of video frames, a registration component for registering each pixel of each facial image with comparable pixels of each of the other facial images, and a restoration component for producing a restored facial image from the facial images. The method includes fitting an active appearance model to a facial image found in each of a plurality of video frames, registering each pixel of each said facial image with comparable pixels of each of the other facial images, and producing a restored facial image from the facial images.
摘要翻译：描述用于执行面部图像恢复的系统和方法。该系统包括用于将活动外观模型拟合到在多个视频帧中的每一个中发现的面部图像的活动外观模型部件，用于将每个面部图像的每个像素与每个其他面部图像的可比较像素对准的注册部件，以及恢复部件，用于从面部图像产生恢复的面部图像。该方法包括将活动外观模型拟合到在多个视频帧中的每一个中发现的面部图像，将每个所述面部图像的每个像素与每个其他面部图像的可比较像素对准，并从面部产生恢复的面部图像图片。

10. 发明授权

US08224037B2 Methods involving face model fitting 有权
标题翻译：涉及面部模型拟合的方法
公开(公告)号：US08224037B2
公开(公告)日：2012-07-17
申请号：US12100620
申请日：2008-04-10
申请人： Xiaoming Liu , Peter Henry Tu , Frederick Wilson Wheeler
发明人： Xiaoming Liu , Peter Henry Tu , Frederick Wilson Wheeler
IPC分类号： G06K9/00
CPC分类号： G06K9/00288 , G06K9/00261 , G06K9/621
摘要： A method for face model fitting comprising, receiving a first observed image, receiving a second observed image, and fitting an active appearance model of a third image to the second observed image and the first observed image with an algorithm that includes a first function of a mean-square-error between a warped image of the second observed image and a synthesis of the active appearance model and a second function of a mean-square-error between the warped image of the second observed image and an appearance data of the first observed image.
摘要翻译：一种用于面部模型拟合的方法，包括：接收第一观察图像，接收第二观察图像，以及使用包括第一观察图像的第一函数的第二观察图像和第一观察图像拟合第三图像的活动外观模型第二观察图像的翘曲图像与活动外观模型的合成之间的均方误差以及第二观察图像的翘曲图像与第一观察图像的外观数据之间的均方误差的第二函数图片。

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