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1. 发明授权

US08705860B2 Grouping variables for fast image labeling 有权
标题翻译：分组变量，用于快速图像标注
公开(公告)号：US08705860B2
公开(公告)日：2014-04-22
申请号：US13046967
申请日：2011-03-14
申请人： Pushmeet Kohli , Sebastian Reinhard Bernhard Nowozin
发明人： Pushmeet Kohli , Sebastian Reinhard Bernhard Nowozin
IPC分类号： G06K9/34 , G06K9/62 , G06K9/68 , G06K9/70
CPC分类号： G06K9/00624
摘要： This application describes grouping variables together to minimize cost or time of performing computer vision analysis techniques on images. In one instance, the pixels of an image are represented by a lattice structure of nodes that are connected to each other by edges. The nodes are grouped or merged together based in part on the energy function associated with each edge that connects the nodes together. The energy function of the edge is based in part on the energy functions associated with each node. The energy functions of the node are based on the possible states in which the node may exist. The states of the node are representative of an object, image, or any other feature or classification that may be associated with the pixels in the image.
摘要翻译：该应用程序将变量分组在一起，以最小化对图像执行计算机视觉分析技术的成本或时间。在一个实例中，图像的像素由通过边缘彼此连接的节点的网格结构来表示。部分地基于与将节点连接在一起的每个边缘相关联的能量函数将节点分组或合并在一起。边缘的能量函数部分地基于与每个节点相关联的能量函数。节点的能量函数基于可能存在节点的可能状态。节点的状态表示可能与图像中的像素相关联的对象，图像或任何其他特征或分类。

2. 发明申请

US20120237127A1 Grouping Variables for Fast Image Labeling 有权
标题翻译：用于快速图像标记的分组变量
公开(公告)号：US20120237127A1
公开(公告)日：2012-09-20
申请号：US13046967
申请日：2011-03-14
申请人： Pushmeet Kohli , Sebastian Reinhard Bernhard Nowozin
发明人： Pushmeet Kohli , Sebastian Reinhard Bernhard Nowozin
IPC分类号： G06K9/34
CPC分类号： G06K9/00624
摘要： This application describes grouping variables together to minimize cost or time of performing computer vision analysis techniques on images. In one instance, the pixels of an image are represented by a lattice structure of nodes that are connected to each other by edges. The nodes are grouped or merged together based in part on the energy function associated with each edge that connects the nodes together. The energy function of the edge is based in part on the energy functions associated with each node. The energy functions of the node are based on the possible states in which the node may exist. The states of the node are representative of an object, image, or any other feature or classification that may be associated with the pixels in the image.
摘要翻译：该应用程序将变量分组在一起，以最小化对图像执行计算机视觉分析技术的成本或时间。在一个实例中，图像的像素由通过边缘彼此连接的节点的网格结构来表示。部分地基于与将节点连接在一起的每个边缘相关联的能量函数将节点分组或合并在一起。边缘的能量函数部分地基于与每个节点相关联的能量函数。节点的能量函数基于可能存在节点的可能状态。节点的状态表示可能与图像中的像素相关联的对象，图像或任何其他特征或分类。

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