公开(公告)号：US20130034295A1

公开(公告)日：2013-02-07

申请号：US13196249

申请日：2011-08-02

Applicant: Masayoshi Tsuchinaga ,  Mario Fritz ,  Trevor Darrell

Inventor： Masayoshi Tsuchinaga ,  Mario Fritz ,  Trevor Darrell

IPC: G06K9/62 ,  G06K9/00 ,  G06K9/46

CPC classification number: G06K9/6857

Abstract: Methods for recognizing a category of an object are disclosed. In one embodiment, a method includes determining, by a processor, a preliminary category of a target object, the preliminary category having a confidence score associated therewith, and comparing the confidence score to a learning threshold. If the highest confidence score is less than the learning threshold, the method further includes estimating properties of the target object and generating a property score for one or more estimated properties, and searching a supplemental image collection for supplemental image data using the preliminary category and the one or more estimated properties. Robots programmed to recognize a category of an object by use of supplemental image data are also disclosed.

Abstract translation: 公开了用于识别对象的类别的方法。 在一个实施例中，一种方法包括由处理器确定目标对象的初始类别，初步类别具有与之相关联的置信度得分，并将置信度分数与学习阈值进行比较。 如果最高可信度得分小于学习阈值，则该方法还包括估计目标对象的属性并生成一个或多个估计属性的属性分数，以及使用初步类别搜索补充图像集合以获得补充图像数据，并且 一个或多个估计属性。 还公开了通过使用补充图像数据来编程来识别对象的类别的机器人。

公开(公告)号：US06445810B2

公开(公告)日：2002-09-03

申请号：US09726425

申请日：2000-12-01

Applicant: Trevor Darrell ,  Gaile Gordon ,  Michael Harville ,  John Woodfill ,  Harlyn Baker

Inventor： Trevor Darrell ,  Gaile Gordon ,  Michael Harville ,  John Woodfill ,  Harlyn Baker

IPC: G06K900

CPC classification number: G06K9/00362

Abstract: Techniques from computer vision and computer graphics are combined to robustly track a target (e.g., a user) and perform a function based upon the image and/or the identity attributed to the target's face. Three primary modules are used to track a user's head: depth estimation, color segmentation, and pattern classification. The combination of these three techniques allows for robust performance despite unknown background, crowded conditions, and rapidly changing pose or expression of the user. Each of the modules can also provide an identity classification module with valuable information so that the identity of a user can be estimated. With an estimate of the position of a target in 3-D and the target's identity, applications such as individualized computer programs or graphics techniques to distort and/or morph the shape or apparent material properties of the user's face can be performed. The system can track and respond to a user's face in real-time using completely passive and non-invasive techniques.

Abstract translation: 来自计算机视觉和计算机图形学的技术被组合以鲁棒地跟踪目标（例如，用户）并且基于归因于目标的脸部的图像和/或身份执行功能。 三个主要模块用于跟踪用户的头部：深度估计，颜色分割和模式分类。 尽管未知背景，拥挤状况以及用户快速变化的姿势或表情，这三种技术的组合也可以实现强大的性能。 每个模块还可以提供具有有价值信息的身份分类模块，以便可以估计用户的身份。 通过估计目标在3D中的位置和目标的身份，可以执行诸如个性化计算机程序或图形技术之类的应用程序来扭曲和/或变形用户脸部的形状或表观材料属性。 该系统可以使用完全无源和非侵入性技术实时跟踪和响应用户的脸部。

公开(公告)号：US08768071B2

公开(公告)日：2014-07-01

申请号：US13196249

申请日：2011-08-02

Applicant: Masayoshi Tsuchinaga ,  Mario Fritz ,  Trevor Darrell

Inventor： Masayoshi Tsuchinaga ,  Mario Fritz ,  Trevor Darrell

IPC: G06K9/68 ,  G06K9/62

CPC classification number: G06K9/6857

Abstract: Methods for recognizing a category of an object are disclosed. In one embodiment, a method includes determining, by a processor, a preliminary category of a target object, the preliminary category having a confidence score associated therewith, and comparing the confidence score to a learning threshold. If the highest confidence score is less than the learning threshold, the method further includes estimating properties of the target object and generating a property score for one or more estimated properties, and searching a supplemental image collection for supplemental image data using the preliminary category and the one or more estimated properties. Robots programmed to recognize a category of an object by use of supplemental image data are also disclosed.

Abstract translation: 公开了用于识别对象的类别的方法。 在一个实施例中，一种方法包括由处理器确定目标对象的初始类别，初步类别具有与之相关联的置信度得分，并将置信度分数与学习阈值进行比较。 如果最高可信度得分小于学习阈值，则该方法还包括估计目标对象的属性并生成一个或多个估计属性的属性分数，以及使用初步类别搜索补充图像集合以获得补充图像数据，并且 一个或多个估计属性。 还公开了通过使用补充图像数据来编程来识别对象的类别的机器人。

公开(公告)号：US06188777B1

公开(公告)日：2001-02-13

申请号：US09102101

申请日：1998-06-22

Applicant: Trevor Darrell ,  Gaile Gordon ,  Michael Harville ,  John Woodfill ,  Harlyn Baker

Inventor： Trevor Darrell ,  Gaile Gordon ,  Michael Harville ,  John Woodfill ,  Harlyn Baker

IPC: G06K900

CPC classification number: G06K9/00362

Abstract: Techniques from computer vision and computer graphics are combined to robustly track a target (e.g., a user) and perform a function based upon the image and/or the identity attributed to the target's face. Three primary modules are used to track a user's head: depth estimation, color segmentation, and pattern classification. The combination of these three techniques allows for robust performance despite unknown background, crowded conditions, and rapidly changing pose or expression of the user. Each of the modules can also provide an identity classification module with valuable information so that the identity of a user can be estimated. With an estimate of the position of a target in 3-D and the target's identity, applications such as individualized computer programs or graphics techniques to distort and/or morph the shape or apparent material properties of the user's face can be performed. The system can track and respond to a user's face in real-time using completely passive and non-invasive techniques.

公开(公告)号：US08704668B1

公开(公告)日：2014-04-22

申请号：US11379268

申请日：2006-04-19

Applicant: Trevor Darrell ,  Anna Hagstrom

Inventor： Trevor Darrell ,  Anna Hagstrom

IPC: G08B23/00

CPC classification number: A01K29/005

Abstract: A system for monitoring and alerting based on animal behavior includes an apparatus to observe one or more animals using a sensor network, a processor to capture tracking information and to interpret animal state based on sensor observations, and a communication device to communicate alerts based on animal state.

Abstract translation: 基于动物行为的用于监测和警报的系统包括使用传感器网络观察一个或多个动物的装置，用于捕获跟踪信息并基于传感器观察来解释动物状态的处理器，以及基于动物来传达警报的通信装置 州。

公开(公告)号：US07317830B1

公开(公告)日：2008-01-08

申请号：US10703393

申请日：2003-11-07

Applicant: Gaile Gordon ,  Trevor Darrell ,  Michael Harville ,  John Woodfill

Inventor： Gaile Gordon ,  Trevor Darrell ,  Michael Harville ,  John Woodfill

IPC: G06K9/34

CPC classification number: G06K9/38 ,  G06T7/11 ,  G06T7/143 ,  G06T7/174 ,  G06T7/194 ,  G06T2207/10021 ,  G06T2207/10028 ,  G06T2207/20224

Abstract: Segmentation of background and foreground objects in an image is based upon the joint use of range and color data. Range-based data is largely independent of color image data, and hence not adversely affected by the limitations associated with color-based segmentation, such as shadows and similarly colored objects. Furthermore, color segmentation is complementary to range measurement in those cases where reliable range data cannot be obtained. These complementary sets of data are used to provide a multidimensional background estimation. The segmentation of a foreground object in a given frame of an image sequence is carried out by comparing the image frames with background statistics relating to range and normalized color, using the sets of statistics in a complementary manner. A background model is determined by estimating using a multidimensional histogram, recording pixel values, configuring the pixel values into a cluster, and selecting a largest cluster as representing the background model.

Abstract translation: 图像中背景和前景对象的分割基于范围和颜色数据的联合使用。 基于范围的数据在很大程度上与彩色图像数据无关，因此不受与基于颜色的分割（例如阴影和类似彩色对象）相关联的限制的不利影响。 此外，在不能获得可靠范围数据的情况下，颜色分割与范围测量是互补的。 这些互补的数据集用于提供多维背景估计。 图像序列的给定帧中的前景对象的分割是通过将图像帧与范围和归一化颜色相关的背景统计数据进行比较，使用互补的统计量集进行的。 背景模型通过使用多维直方图估计，记录像素值，将像素值配置到聚类中，并选择最大的聚类来表示背景模型来确定。

公开(公告)号：US20050265583A1

公开(公告)日：2005-12-01

申请号：US11195039

申请日：2005-08-01

Applicant: Michele Covell ,  Michael Lin ,  Ali Rahimi ,  Michael Harville ,  Trevor Darrell ,  John Woodfill ,  Harlyn Baker ,  Gaile Gordon

Inventor： Michele Covell ,  Michael Lin ,  Ali Rahimi ,  Michael Harville ,  Trevor Darrell ,  John Woodfill ,  Harlyn Baker ,  Gaile Gordon

IPC: G06K9/00 ,  G06T7/00 ,  G06T7/20

CPC classification number: G06K9/00375 ,  G06K9/00369 ,  G06T7/251 ,  G06T7/75 ,  G06T2207/10016 ,  G06T2207/30196

Abstract: Dense range data obtained at real-time rates is employed to estimate the pose of an articulated figure. In one approach, the range data is used in combination with a model of connected patches. Each patch is the planar convex hull of two circles, and a recursive procedure is carried out to determine an estimate of pose which most closely correlates to the range data. In another aspect of the invention, the dense range data is used in conjunction with image intensity information to improve pose tracking performance. The range information is used to determine the shape of an object, rather than assume a generic model or estimate structure from motion. In this aspect of the invention, a depth constraint equation, which is a counterpart to the classic brightness change constraint equation, is employed. Both constraints are used to jointly solve for motion estimates.

Abstract translation: 采用实时速率获得的浓度范围数据来估计关节数字的姿态。 在一种方法中，范围数据与连接补丁的模型结合使用。 每个贴片是两个圆的平面凸包，并且执行递归过程以确定与范围数据最密切相关的姿势的估计。 在本发明的另一方面，密集范围数据与图像强度信息结合使用以改善姿态跟踪性能。 范围信息用于确定对象的形状，而不是假设通用模型或从运动估计结构。 在本发明的这个方面，采用与经典亮度变化约束方程相对应的深度约束方程。 两个约束都用于共同解决运动估计。

公开(公告)号：US06356669B1

公开(公告)日：2002-03-12

申请号：US09318790

申请日：1999-05-26

Applicant: Trevor Darrell

Inventor： Trevor Darrell

IPC: G06K932

CPC classification number: G06T17/00

Abstract: Image-based synthesis for non-rigid bodies whose appearances do not form a linear manifold is carried out by representing mappings from control parameters to appearances as subsets of piecewise smooth functions. Each subset contains example images which are well approximated by particular examples which lie on the convex hull of the subset's parameter values. Once the subsets of examples are defined, interpolation is performed by using only the examples in a single subset. To provide for efficient operation, image transforms based upon radial cumulative similarities are used to automatically estimate the correspondence between example images.

Abstract translation: 通过将从控制参数到外观的映射表示为分段平滑函数的子集来执行外观不形成线性歧管的非刚性体的基于图像的合成。 每个子集包含通过位于子集参数值的凸包上的特定实例很好地近似的示例图像。 一旦定义了示例子集，就可以通过仅使用单个子集中的示例来执行内插。 为了提供有效的操作，使用基于径向累积相似度的图像变换来自动估计示例图像之间的对应关系。

公开(公告)号：US20050162523A1

公开(公告)日：2005-07-28

申请号：US10762941

申请日：2004-01-22

Applicant: Trevor Darrell ,  Tom Yeh ,  Konrad Tollmar

Inventor： Trevor Darrell ,  Tom Yeh ,  Konrad Tollmar

IPC: G06F17/30 ,  H04N5/232

CPC classification number: G06F17/30277 ,  G06F17/30864

Abstract: A mobile deixis device includes a camera to capture an image and a wireless handheld device, coupled to the camera and to a wireless network, to communicate the image with existing databases to find similar images. The mobile deixis device further includes a processor, coupled to the device, to process found database records related to similar images and a display to view found database records that include web pages including images. With such an arrangement, users can specify a location of interest by simply pointing a camera-equipped cellular phone at the object of interest and by searching an image database or relevant web resources, users can quickly identify good matches from several close ones to find an object of interest.

Abstract translation: 移动指示设备包括用于捕获图像的相机和耦合到相机和无线网络的无线手持设备，以将图像与现有数据库通信以找到相似的图像。 移动指示设备还包括耦合到该设备的处理器，以处理与类似图像相关的发现的数据库记录和显示器，以查看包括包括图像的网页的发现的数据库记录。 通过这样的布置，用户可以通过简单地将配备有相机的蜂窝电话指向感兴趣的对象并且通过搜索图像数据库或相关网络资源来指定感兴趣的位置，用户可以快速地从几个密切的识别符中找到良好的匹配，以找到 感兴趣的对象

公开(公告)号：US06661918B1

公开(公告)日：2003-12-09

申请号：US09453450

申请日：1999-12-03

Applicant: Gaile Gordon ,  Michael Harville ,  John Woodfill ,  Trevor Darrell

Inventor： Gaile Gordon ,  Michael Harville ,  John Woodfill ,  Trevor Darrell

IPC: G06K934

CPC classification number: G06K9/38 ,  G06T7/11 ,  G06T7/143 ,  G06T7/174 ,  G06T7/194 ,  G06T2207/10021 ,  G06T2207/10028 ,  G06T2207/20224

Abstract: Segmentation of background and foreground objects in an image is based upon the joint use of both range and color data. Range-based data is largely independent of color image data, and hence not adversely affected by the limitations associated with color-based segmentation, such as shadows and similarly colored objects. Furthermore, color segmentation is complementary to range measurement in those cases where reliable range data cannot be obtained. These complementary sets of data are used to provide a multidimensional background estimation. The segmentation of a foreground object in a given frame of an image sequence is carried out by comparing the image frames with background statistics relating to range and normalized color, using the sets of statistics in a complementary manner.

Abstract translation: 图像中背景和前景对象的分割基于范围和颜色数据的联合使用。 基于范围的数据在很大程度上与彩色图像数据无关，因此不受与基于颜色的分割（例如阴影和类似彩色对象）相关联的限制的不利影响。 此外，在不能获得可靠范围数据的情况下，颜色分割与范围测量是互补的。 这些互补的数据集用于提供多维背景估计。 图像序列的给定帧中的前景对象的分割是通过将图像帧与范围和归一化颜色相关的背景统计数据进行比较，使用互补的统计量集进行的。