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1. 发明申请

US20150163477A1 SYSTEMS AND METHODS FOR CALCULATING EPIPOLAR CONSTRAINTS BETWEEN GENERALIZED CAMERAS 审中-公开
标题翻译：一般摄像机计算不确定因素的系统与方法
公开(公告)号：US20150163477A1
公开(公告)日：2015-06-11
申请号：US13372559
申请日：2012-02-14
申请人： Bryan Klingner , David Martin , Scott Ettinger
发明人： Bryan Klingner , David Martin , Scott Ettinger
IPC分类号： H04N13/02 , H04N5/353 , G06T15/20
CPC分类号： G06T7/593
摘要： Methods and systems for calculating epipolar constraints between a plurality of generalized cameras are provided. Each generalized camera implements two pixel projection functions. One function converts a known pixel location into a ray emanating from a projection center of a first camera to a point on a feature at the pixel location. Another function converts a three dimensional point on the feature in Euclidean space to a pixel location on a projection of the feature in the image space of a second camera. Subsegments of along the ray are projected onto the image space of the second camera and are subdivided until each subsegment spans no more than one pixel in the second camera's image space. The endpoints of all subsegments are projected into the image space of the second camera and the discrete pixel locations of each subsegment are recorded to form epipolar zones.
摘要翻译：提供了用于计算多个广义照相机之间的对极约束的方法和系统。每个广义摄像机实现两个像素投影功能。一个功能将已知像素位置转换成从第一相机的投影中心发射到在像素位置处的特征上的点的光线。另一个函数将欧氏空间中的特征上的三维点转换成第二相机的图像空间中的特征的投影上的像素位置。沿着光线的子段被投影到第二照相机的图像空间上，并被细分，直到每个子段跨越第二相机的图像空间中不超过一个像素。所有子段的端点投影到第二相机的图像空间中，并且记录每个子段的离散像素位置以形成对极区。

2. 发明授权

US09135715B1 Local feature cameras for structure from motion (SFM) problems with generalized cameras 有权
标题翻译：用于通用摄像机的运动结构（SFM）问题的本地功能摄像机
公开(公告)号：US09135715B1
公开(公告)日：2015-09-15
申请号：US13427121
申请日：2012-03-22
申请人： Bryan Klingner , David Martin
发明人： Bryan Klingner , David Martin
IPC分类号： G06K9/00 , G06T7/20 , H04N5/232
CPC分类号： G06T7/20 , G06T7/593 , G06T2207/10012 , H04N5/2329
摘要： Methods and systems for extraction of 3D geometry from a plurality of generalized camera images by a device that comprises an electronic circuit are provided. Methods include identifying an x and y coordinate, an orientation, and a scale for each of one or more feature locations in each of the generalized camera images, extracting a local image feature at each feature location, generating a feature camera centered on each feature location, identifying groups of feature cameras providing consistent triangulation opportunity, and triangulating each identified feature camera group by finding the 3D point that minimizes an error term.
摘要翻译：提供了通过包括电子电路的装置从多个广义摄像机图像中提取3D几何的方法和系统。方法包括识别每个广义摄像机图像中的一个或多个特征位置中的每一个的x和y坐标，方向和比例，在每个特征位置提取局部图像特征，生成以每个特征位置为中心的特征照相机识别提供一致的三角测量机会的特征摄像机组，并通过找到最小化误差项的3D点来对每个识别的特征摄像机组进行三角测量。

3. 发明授权

US11544299B2 Topological basemodel supporting improved conflation and stable feature identity 有权
公开(公告)号：US11544299B2
公开(公告)日：2023-01-03
申请号：US17251071
申请日：2020-03-02
申请人： Google LLC , Christine McGavran , Richard William Bukowski , Bryan Klingner , Joakim Kristian Olle Arfvidsson , Andrew Lookingbill
发明人： Christine McGavran , Richard William Bukowski , Bryan Klingner , Joakim Kristian Olle Arfvidsson , Andrew Lookingbill
IPC分类号： G06F16/00 , G06F16/29 , G06F16/22
摘要： The present disclosure is directed to systems and methods for providing a stable topological representation of pathway networks as well as features associated with these networks. The disclosure is exemplified using road networks which have applications in mapping, navigation, and autonomous vehicles. Extensions may be learned through practice of the disclosure. Utilizing implementations disclosed herein may provide advantages for data conflation between different mapping systems and map data while improving overall stability by developing a common reference standard that is tied to semantic features rather than abstract geographic representations.

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