公开(公告)号：US09530235B2

公开(公告)日：2016-12-27

申请号：US14546217

申请日：2014-11-18

Applicant: Google Inc.

Inventor： Dennis Strelow ,  Craig Lewin Robinson ,  Samuel Felix de Sousa, Jr.

IPC: G06T11/60 ,  G06T3/00 ,  G06T7/00

CPC classification number: G06T11/60 ,  G06T3/0068 ,  G06T7/30

Abstract: Systems and methods for aligning panoramic imagery of a geographic area captured from a perspective at or near ground level and aerial imagery captured from an oblique perspective are provided. More particularly, a facade plane can be detected in a panoramic image based at least in part on geometric data associated with the image. The panoramic image can also have an associated image pose. An aerial image depicting the same facade can then be identified. The aerial image can be associated with an image pose and geometric data of the depicted imagery. The panoramic image can be warped into an image having a perspective associated with the aerial image. One or more feature matches between the warped image and the aerial image can be identified using a feature matching technique. The matched features can be used to align the panoramic image with the aerial image.

Abstract translation: 提供了从倾斜角度捕获的从地面或附近观察到的地理区域的全景图像对准的空间图像的系统和方法。 更具体地，可以至少部分地基于与图像相关联的几何数据，在全景图像中检测立面平面。 全景图像也可以具有相关联的图像姿势。 然后可以识别描绘相同立面的空中图像。 空中图像可以与所描绘的图像的图像姿态和几何数据相关联。 全景图像可以变形成具有与航空图像相关联的透视图像。 弯曲图像和空中图像之间的一个或多个特征匹配可以使用特征匹配技术来识别。 匹配的功能可用于将全景图像与空中图像对齐。

公开(公告)号：US20160140744A1

公开(公告)日：2016-05-19

申请号：US14546217

申请日：2014-11-18

Applicant: GOOGLE INC.

Inventor： Dennis Strelow ,  Craig Lewin Robinson ,  Samuel Felix de Sousa, JR.

IPC: G06T11/60

CPC classification number: G06T11/60 ,  G06T3/0068 ,  G06T7/30

Abstract: Systems and methods for aligning panoramic imagery of a geographic area captured from a perspective at or near ground level and aerial imagery captured from an oblique perspective are provided. More particularly, a facade plane can be detected in a panoramic image based at least in part on geometric data associated with the image. The panoramic image can also have an associated image pose. An aerial image depicting the same facade can then be identified. The aerial image can be associated with an image pose and geometric data of the depicted imagery. The panoramic image can be warped into an image having a perspective associated with the aerial image. One or more feature matches between the warped image and the aerial image can be identified using a feature matching technique. The matched features can be used to align the panoramic image with the aerial image.

Abstract translation: 提供了从倾斜角度捕获的从地面或附近观察到的地理区域的全景图像对准的空间图像的系统和方法。 更具体地，可以至少部分地基于与图像相关联的几何数据，在全景图像中检测立面平面。 全景图像也可以具有相关联的图像姿势。 然后可以识别描绘相同立面的空中图像。 空中图像可以与所描绘的图像的图像姿态和几何数据相关联。 全景图像可以变形成具有与航空图像相关联的透视图像。 弯曲图像和空中图像之间的一个或多个特征匹配可以使用特征匹配技术来识别。 匹配的功能可用于将全景图像与空中图像对齐。

公开(公告)号：US09569847B1

公开(公告)日：2017-02-14

申请号：US14622623

申请日：2015-02-13

Applicant: Google Inc.

Inventor： Dennis Strelow ,  Jay Yagnik

IPC: G06K9/00 ,  G06T7/00 ,  G06F17/16

CPC classification number: G06F17/16 ,  G06F17/11 ,  G06T7/246 ,  G06T7/70 ,  G06T7/73 ,  G06T2207/10016 ,  G06T2207/30244

Abstract: One of the described methods includes receiving a plurality of images from a camera, the plurality of images comprising a sequence; identifying one or more two-dimensional features in each of a plurality of images in the received sequence of images; associating a three-dimensional point with each of the identified one or more two-dimensional features; tracking each of the one or more two-dimensional features through successive images in the plurality of images; and iteratively minimizing a two-dimensional image error between the tracked each of the one or more two-dimensional features and an image reprojection with respect to the three-dimensional point corresponding to the one or more two-dimensional features and a three-dimensional position of the camera corresponding to one or more of the plurality of images.

Abstract translation: 所描述的方法之一包括从相机接收多个图像，所述多个图像包括序列; 识别所接收的图像序列中的多个图像中的每一个中的一个或多个二维特征; 将三维点与所识别的一个或多个二维特征中的每一个相关联; 通过所述多个图像中的连续图像跟踪所述一个或多个二维特征中的每一个; 并且迭代地最小化所述一个或多个二维特征中的所跟踪的每个之间的二维图像误差和相对于对应于所述一个或多个二维特征的三维点的图像重投影，以及三维位置 所述相机对应于所述多个图像中的一个或多个。

公开(公告)号：US09202137B2

公开(公告)日：2015-12-01

申请号：US14260966

申请日：2014-04-24

Applicant: Google Inc.

Inventor： Luca Bertelli ,  Dennis Strelow ,  Sally A. Goldman

IPC: G06K9/00 ,  G06K9/62

CPC classification number: G06K9/6202 ,  G06K9/4642 ,  G06K9/4652 ,  G06K2009/6213

Abstract: A method for determining a salient region of an image is disclosed. For a plurality of different saliency cue functions, a single saliency value is calculated for each pixel in a plurality of adjacent pixels in an image using the saliency cue function, wherein one of the saliency cue functions is based on whether the pixel is in a region of the image whose colors contrast with the region's background and another of the saliency cue functions is based on a foreground and background color models of the image. A classifier is used to calculate a combined single saliency value for each pixel based on the single saliency values for the pixel. The salient region of the pixels is determined with a subwindow search based on the combined single saliency values.

Abstract translation: 公开了一种用于确定图像的显着区域的方法。 对于多个不同的显着提示功能，使用显着性提示功能为图像中的多个相邻像素中的每个像素计算单个显着值，其中显着性提示功能之一是基于像素是否在区域 其颜色与区域的背景对比的图像和其他显着提示功能基于图像的前景和背景颜色模型。 分类器用于基于像素的单个显着值来计算每个像素的组合单显着值。 基于组合的单个显着值的子窗口搜索确定像素的显着区域。

公开(公告)号：US20150169989A1

公开(公告)日：2015-06-18

申请号：US14260966

申请日：2014-04-24

Applicant: Google Inc.

Inventor： Luca Bertelli ,  Dennis Strelow ,  Sally A. Goldman

IPC: G06K9/62

CPC classification number: G06K9/6202 ,  G06K9/4642 ,  G06K9/4652 ,  G06K2009/6213

Abstract: A method for determining a salient region of an image is disclosed. For a plurality of different saliency cue functions, a single saliency value is calculated for each pixel in a plurality of adjacent pixels in an image using the saliency cue function, wherein one of the saliency cue functions is based on whether the pixel is in a region of the image whose colors contrast with the region's background and another of the saliency cue functions is based on a foreground and background color models of the image. A classifier is used to calculate a combined single saliency value for each pixel based on the single saliency values for the pixel. The salient region of the pixels is determined with a subwindow search based on the combined single saliency values.

Abstract translation: 公开了一种用于确定图像的显着区域的方法。 对于多个不同的显着提示功能，使用显着性提示功能为图像中的多个相邻像素中的每个像素计算单个显着值，其中显着性提示功能之一是基于像素是否在区域 其颜色与区域的背景对比的图像和其他显着提示功能基于图像的前景和背景颜色模型。 分类器用于基于像素的单个显着值来计算每个像素的组合单显着值。 基于组合的单个显着值的子窗口搜索确定像素的显着区域。