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1. 发明授权

US07430315B2 Face recognition system 有权
标题翻译：人脸识别系统
公开(公告)号：US07430315B2
公开(公告)日：2008-09-30
申请号：US10858930
申请日：2004-06-01
申请人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Takahiro Ohashi
发明人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Takahiro Ohashi
IPC分类号： G06K9/62 , G06K9/64 , G06K9/40
CPC分类号： G06K9/6269 , G06K9/00228 , G06K9/6857
摘要： The face detection system and method attempts classification of a test image before performing all of the kernel evaluations. Many subimages are not faces and should be relatively easy to identify as such. Thus, the SVM classifier try to discard non-face images using as few kernel evaluations as possible using a cascade SVM classification. In the first stage, a score is computed for the first two support vectors, and the score is compared to a threshold. If the score is below the threshold value, the subimage is classified as not a face. If the score is above the threshold value, the cascade SVM classification function continues to apply more complicated decision rules, each time doubling the number of kernel evaluations, classifying the image as a non-face (and thus terminating the process) as soon as the test image fails to satisfy one of the decision rules. Finally, if the subimage has satisfied all intermediary decision rules, and has now reached the point at which all support vectors must be considered, the original decision function is applied. Satisfying this final rule, and all intermediary rules, is the only way for a test image to garner a positive (face) classification.
摘要翻译：面部检测系统和方法在执行所有内核评估之前尝试对测试图像进行分类。许多子图像不是面孔，应该比较容易识别。因此，SVM分类器尝试使用级联SVM分类使用尽可能少的内核评估来丢弃非面部图像。在第一阶段，对前两个支持向量计算分数，并将分数与阈值进行比较。如果分数低于阈值，则子图像被分类为不是脸部。如果分数高于阈值，则级联SVM分类功能继续应用更复杂的决策规则，每次将内核评估的数量加倍，将图像分类为非面（并因此终止进程），一旦测试图像不能满足其中一个决策规则。最后，如果子图像满足了所有的中介决策规则，并且现在已经到了必须考虑所有支持向量的点，则应用原始决策函数。满足这个最终规则和所有中介规则是测试图像获得积极（面部）分类的唯一方法。

2. 发明申请

US20050180627A1 Face recognition system 有权
标题翻译：人脸识别系统
公开(公告)号：US20050180627A1
公开(公告)日：2005-08-18
申请号：US10858930
申请日：2004-06-01
申请人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Takahiro Ohashi
发明人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Takahiro Ohashi
IPC分类号： G06K9/00 , G06K9/62 , G06K9/68 , G06K9/74
CPC分类号： G06K9/6269 , G06K9/00228 , G06K9/6857
摘要： The face detection system and method attempts classification of a test image before performing all of the kernel evaluations. Many subimages are not faces and should be relatively easy to identify as such. Thus, the SVM classifier try to discard non-face images using as few kernel evaluations as possible using a cascade SVM classification. In the first stage, a score is computed for the first two support vectors, and the score is compared to a threshold. If the score is below the threshold value, the subimage is classified as not a face. If the score is above the threshold value, the cascade SVM classification function continues to apply more complicated decision rules, each time doubling the number of kernel evaluations, classifying the image as a non-face (and thus terminating the process) as soon as the test image fails to satisfy one of the decision rules. Finally, if the subimage has satisfied all intermediary decision rules, and has now reached the point at which all support vectors must be considered, the original decision function is applied. Satisfying this final rule, and all intermediary rules, is the only way for a test image to garner a positive (face) classification.
摘要翻译：面部检测系统和方法在执行所有内核评估之前尝试对测试图像进行分类。许多子图像不是面孔，应该比较容易识别。因此，SVM分类器尝试使用级联SVM分类使用尽可能少的内核评估来丢弃非面部图像。在第一阶段，对前两个支持向量计算分数，并将分数与阈值进行比较。如果分数低于阈值，则子图像被分类为不是脸部。如果分数高于阈值，则级联SVM分类功能继续应用更复杂的决策规则，每次将内核评估的数量加倍，将图像分类为非面（并因此终止进程），一旦测试图像不能满足其中一个决策规则。最后，如果子图像满足了所有的中介决策规则，并且现在已经到了必须考虑所有支持向量的点，则应用原始决策函数。满足这个最终规则和所有中介规则是测试图像获得积极（面部）分类的唯一方法。

3. 发明申请

US20050180602A1 Method, apparatus and program for detecting an object 有权
标题翻译：用于检测物体的方法，装置和程序
公开(公告)号：US20050180602A1
公开(公告)日：2005-08-18
申请号：US10858878
申请日：2004-06-01
申请人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Takahiro Ohashi
发明人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Takahiro Ohashi
IPC分类号： G06K9/00 , G06K9/36 , G06K9/48
CPC分类号： G06K9/00201
摘要： The advantage of the present invention is to appropriately detect the object. The object detection apparatus in the present invention has a plurality of cameras to determine the distance to the objects, a distance determination unit to determine the distance therein, a histogram generation unit to specify the frequency of the pixels against the distances to the pixels, an object distance determination unit that determines the most likely distance, a probability mapping unit that provides the probabilities of the pixels based on the difference of the distance, a kernel detection unit that determines a kernel region as a group of the pixels, a periphery detection unit that determines a peripheral region as a group of the pixels, selected from the pixels being close to the kernel region and an object specifying unit that specifies the object region where the object is present with a predetermined probability.
摘要翻译：本发明的优点是适当地检测物体。本发明的物体检测装置具有多个照相机，用于确定与物体的距离，距离确定单元，用于确定其中的距离;直方图生成单元，用于根据与像素的距离来指定像素的频率; 确定最可能的距离的对象距离确定单元，基于距离差提供像素概率的概率映射单元，将核区域确定为像素组的内核检测单元，周边检测单元将外围区域确定为从接近核心区域的像素中选择的像素组，以及以预定概率指定对象存在的对象区域的对象指定单元。

4. 发明授权

US07224831B2 Method, apparatus and program for detecting an object 有权
标题翻译：用于检测物体的方法，装置和程序
公开(公告)号：US07224831B2
公开(公告)日：2007-05-29
申请号：US10858878
申请日：2004-06-01
申请人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Takahiro Ohashi
发明人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Takahiro Ohashi
IPC分类号： G06K9/36
CPC分类号： G06K9/00201
摘要： The advantage of the present invention is to appropriately detect the object. The object detection apparatus in the present invention has a plurality of cameras to determine the distance to the objects, a distance determination unit to determine the distance therein, a histogram generation unit to specify the frequency of the pixels against the distances to the pixels, an object distance determination unit that determines the most likely distance, a probability mapping unit that provides the probabilities of the pixels based on the difference of the distance, a kernel detection unit that determines a kernel region as a group of the pixels, a periphery detection unit that determines a peripheral region as a group of the pixels, selected from the pixels being close to the kernel region and an object specifying unit that specifies the object region where the object is present with a predetermined probability.
摘要翻译：本发明的优点是适当地检测物体。本发明的物体检测装置具有多个照相机，用于确定与物体的距离，距离确定单元，用于确定其中的距离;直方图生成单元，用于根据与像素的距离来指定像素的频率; 确定最可能的距离的对象距离确定单元，基于距离差提供像素概率的概率映射单元，将核区域确定为像素组的内核检测单元，周边检测单元将外围区域确定为从接近核心区域的像素中选择的像素组，以及以预定概率指定对象存在的对象区域的对象指定单元。

5. 发明授权

US07369682B2 Adaptive discriminative generative model and application to visual tracking 有权
标题翻译：自适应识别生成模型和应用于视觉跟踪
公开(公告)号：US07369682B2
公开(公告)日：2008-05-06
申请号：US11179881
申请日：2005-07-11
申请人： Ming-Hsuan Yang , Ruei-Sung Lin , Jongwoo Lim , David Ross
发明人： Ming-Hsuan Yang , Ruei-Sung Lin , Jongwoo Lim , David Ross
IPC分类号： G06K9/00
CPC分类号： G06K9/00241 , G06K9/00261 , G06K9/3233 , G06K9/6214 , G06K9/6234 , G06K9/6247 , G06T7/246 , G06T7/277 , G06T7/70 , G06T2207/30241
摘要： A system and a method are disclosed for an adaptive discriminative generative model with a probabilistic interpretation. As applied to visual tracking, the discriminative generative model separates the target object from the background more accurately and efficiently than conventional methods. A computationally efficient algorithm constantly updates the discriminative model over time. The discriminative generative model adapts to accommodate dynamic appearance variations of the target and background. Experiments show that the discriminative generative model effectively tracks target objects undergoing large pose and lighting changes.
摘要翻译：公开了一种具有概率解释的自适应识别生成模型的系统和方法。应用于视觉跟踪，鉴别生成模型比传统方法更准确有效地将目标对象与背景分离。计算有效的算法随着时间不断更新辨别模型。鉴别生成模型适应于适应目标和背景的动态外观变化。实验表明，识别性生成模型有效地跟踪目标物体的大姿态和照明变化。

6. 发明授权

US07463754B2 Adaptive probabilistic visual tracking with incremental subspace update 有权
标题翻译：具有增量子空间更新的自适应概率视觉跟踪
公开(公告)号：US07463754B2
公开(公告)日：2008-12-09
申请号：US10989966
申请日：2004-11-15
申请人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Ruei-Sung Lin
发明人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Ruei-Sung Lin
IPC分类号： G06K9/00
CPC分类号： G06K9/621 , G06K9/3241 , G06T7/207
摘要： A system and a method are disclosed for adaptive probabilistic tracking of an object within a motion video. The method utilizes a time-varying Eigenbasis and dynamic, observation and inference models. The Eigenbasis serves as a model of the target object. The dynamic model represents the motion of the object and defines possible locations of the target based upon previous locations. The observation model provides a measure of the distance of an observation of the object relative to the current Eigenbasis. The inference model predicts the most likely location of the object based upon past and present observations. The method is effective with or without training samples. A computer-based system provides a means for implementing the method. The effectiveness of the system and method are demonstrated through simulation.
摘要翻译：公开了用于运动视频内的对象的自适应概率跟踪的系统和方法。该方法利用时变特征向量和动态，观察和推理模型。 Eigenbasis作为目标对象的模型。动态模型表示对象的运动，并根据先前的位置定义目标的可能位置。观察模型提供了对象相对于当前Eigenbasis的观察距离的度量。推论模型基于过去和现在的观察预测对象的最可能的位置。该方法在有或没有训练样本的情况下是有效的。基于计算机的系统提供了实现该方法的手段。通过仿真证明了系统和方法的有效性。

7. 发明申请

US20060036399A1 Adaptive discriminative generative model and application to visual tracking 有权
标题翻译：自适应识别生成模型和应用于视觉跟踪
公开(公告)号：US20060036399A1
公开(公告)日：2006-02-16
申请号：US11179881
申请日：2005-07-11
申请人： Ming-Hsuan Yang , Ruei-Sung Lin , Jongwoo Lim , David Ross
发明人： Ming-Hsuan Yang , Ruei-Sung Lin , Jongwoo Lim , David Ross
IPC分类号： G06F17/18
CPC分类号： G06K9/00241 , G06K9/00261 , G06K9/3233 , G06K9/6214 , G06K9/6234 , G06K9/6247 , G06T7/246 , G06T7/277 , G06T7/70 , G06T2207/30241
摘要： A system and a method are disclosed for an adaptive discriminative generative model with a probabilistic interpretation. As applied to visual tracking, the discriminative generative model separates the target object from the background more accurately and efficiently than conventional methods. A computationally efficient algorithm constantly updates the discriminative model over time. The discriminative generative model adapts to accommodate dynamic appearance variations of the target and background. Experiments show that the discriminative generative model effectively tracks target objects undergoing large pose and lighting changes.
摘要翻译：公开了一种具有概率解释的自适应识别生成模型的系统和方法。应用于视觉跟踪，鉴别生成模型比传统方法更准确有效地将目标对象与背景分离。计算有效的算法随着时间不断更新辨别模型。鉴别生成模型适应于适应目标和背景的动态外观变化。实验表明，识别性生成模型有效地跟踪目标物体的大姿态和照明变化。

8. 发明申请

US20050175219A1 Adaptive probabilistic visual tracking with incremental subspace update 有权
标题翻译：具有增量子空间更新的自适应概率视觉跟踪
公开(公告)号：US20050175219A1
公开(公告)日：2005-08-11
申请号：US10989966
申请日：2004-11-15
申请人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Ruei-Sung Lin
发明人： Ming-Hsuan Yang , Jongwoo Lim , David Ross , Ruei-Sung Lin
IPC分类号： G06K9/00 , G06K9/46 , G06T7/20
CPC分类号： G06K9/621 , G06K9/3241 , G06T7/207
摘要： A system and a method are disclosed for adaptive probabilistic tracking of an object within a motion video. The method utilizes a time-varying Eigenbasis and dynamic, observation and inference models. The Eigenbasis serves as a model of the target object. The dynamic model represents the motion of the object and defines possible locations of the target based upon previous locations. The observation model provides a measure of the distance of an observation of the object relative to the current Eigenbasis. The inference model predicts the most likely location of the object based upon past and present observations. The method is effective with or without training samples. A computer-based system provides a means for implementing the method. The effectiveness of the system and method are demonstrated through simulation.
摘要翻译：公开了用于运动视频内的对象的自适应概率跟踪的系统和方法。该方法利用时变特征向量和动态，观察和推理模型。 Eigenbasis作为目标对象的模型。动态模型表示对象的运动，并根据先前的位置定义目标的可能位置。观察模型提供了对象相对于当前Eigenbasis的观察距离的度量。推论模型基于过去和现在的观察预测对象的最可能的位置。该方法在有或没有训练样本的情况下是有效的。基于计算机的系统提供了实现该方法的手段。通过仿真证明了系统和方法的有效性。

9. 发明授权

US07623731B2 Direct method for modeling non-rigid motion with thin plate spline transformation 有权
标题翻译：用薄板样条变换建立非刚性运动的直接方法
公开(公告)号：US07623731B2
公开(公告)日：2009-11-24
申请号：US11450045
申请日：2006-06-09
申请人： Jongwoo Lim , Ming-Hsuan Yang
发明人： Jongwoo Lim , Ming-Hsuan Yang
IPC分类号： G06K9/36
CPC分类号： G06T7/20 , G06K9/6206
摘要： A system and a method model the motion of a non-rigid object using a thin plate spline (TPS) transform. A first image of a video sequence is received, and a region of interest, referred to as a template, is chosen manually or automatically. A set of arbitrarily-chosen fixed reference points is positioned on the template. A target image of the video sequence is chosen for motion estimation relative to the template. A set of pixels in the target image corresponding to the pixels of the template is determined, and this set of pixels is back-warped to match the template using a thin-plate-spline-based technique. The error between the template and the back-warped image is determined and iteratively minimized using a gradient descent technique. The TPS parameters can then be used to estimate the relative motion between the template and the corresponding region of the target image. According to one embodiment, a stiff-to-flexible approach mitigates instability that can arise when reference points lie in textureless regions, or when the initial TPS parameters are not close to the desired ones. The value of a regularization parameter is varied from a larger to a smaller value, varying the nature of the warp from stiff to flexible, so as to progressively emphasize local non-rigid deformations.
摘要翻译：一种使用薄板样条（TPS）变换建立非刚性物体的运动的系统和方法。接收视频序列的第一图像，并且手动地或自动地选择被称为模板的感兴趣区域。一组任意选择的固定参考点位于模板上。选择视频序列的目标图像用于相对于模板的运动估计。确定与模板的像素相对应的目标图像中的一组像素，并且使用基于薄板样条的技术来使该组像素逆向匹配模板。使用梯度下降技术确定模板和反翘曲图像之间的误差并迭代地最小化。然后可以使用TPS参数来估计模板和目标图像的对应区域之间的相对运动。根据一个实施例，柔性到柔性的方法减轻了当参考点位于无纹理区域时或者当初始TPS参数不接近期望的区域时可能出现的不稳定性。正则化参数的值从较大值变化到较小值，将翘曲的性质从刚性变化到柔性，从而逐渐强调局部非刚性变形。

10. 发明申请

US20060285770A1 Direct method for modeling non-rigid motion with thin plate spline transformation 有权
公开(公告)号：US20060285770A1
公开(公告)日：2006-12-21
申请号：US11450045
申请日：2006-06-09
申请人： Jongwoo Lim , Ming-Hsuan Yang
发明人： Jongwoo Lim , Ming-Hsuan Yang
IPC分类号： G06K9/36 , G06K9/00
CPC分类号： G06T7/20 , G06K9/6206
摘要： A system and a method model the motion of a non-rigid object using a thin plate spline (TPS) transform. A first image of a video sequence is received, and a region of interest, referred to as a template, is chosen manually or automatically. A set of arbitrarily-chosen fixed reference points is positioned on the template. A target image of the video sequence is chosen for motion estimation relative to the template. A set of pixels in the target image corresponding to the pixels of the template is determined, and this set of pixels is back-warped to match the template using a thin-plate-spline-based technique. The error between the template and the back-warped image is determined and iteratively minimized using a gradient descent technique. The TPS parameters can then be used to estimate the relative motion between the template and the corresponding region of the target image. According to one embodiment, a stiff-to-flexible approach mitigates instability that can arise when reference points lie in textureless regions, or when the initial TPS parameters are not close to the desired ones. The value of a regularization parameter is varied from a larger to a smaller value, varying the nature of the warp from stiff to flexible, so as to progressively emphasize local non-rigid deformations.

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