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公开(公告)号：US09384402B1
公开(公告)日：2016-07-05
申请号：US14249611
申请日：2014-04-10
Applicant: Google Inc.
Inventor： Vadim Furman , Andrew Hughes Chatham , Abhijit Ogale , Dmitri Dolgov
CPC classification number: G06K9/00805 , B60R11/04 , B60R2011/0026 , B60R2011/004 , B60R2011/008 , G01C21/00 , G01C21/30 , G06K9/00791 , G06K9/6202 , G06T9/00 , H04N19/117 , H04N19/136 , H04N19/167 , H04N19/17 , H04N19/85
Abstract: A vehicle may receive one or more images of an environment of the vehicle. The vehicle may also receive a map of the environment. The vehicle may also match at least one feature in the one or more images with corresponding one or more features in the map. The vehicle may also identify a given area in the one or more images that corresponds to a portion of the map that is within a threshold distance to the one or more features. The vehicle may also compress the one or more images to include a lower amount of details in areas of the one or more images other than the given area. The vehicle may also provide the compressed images to a remote system, and responsively receive operation instructions from the remote system.
Abstract translation: 车辆可以接收车辆的环境的一个或多个图像。 车辆还可以接收环境地图。 车辆还可以将一个或多个图像中的至少一个特征与图中的相应的一个或多个特征进行匹配。 车辆还可以识别与一个或多个特征的阈值距离内的对应于地图的一部分的一个或多个图像中的给定区域。 车辆还可以压缩一个或多个图像以在除了给定区域之外的一个或多个图像的区域中包括较少量的细节。 车辆还可以将压缩图像提供给远程系统，并且响应地接收来自远程系统的操作指令。
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12.发明授权公开(公告)号：US09349055B1
公开(公告)日：2016-05-24
申请号：US13927225
申请日：2013-06-26
Applicant: Google Inc.
Inventor： Abhijit Ogale
IPC: G06K9/00
CPC classification number: G05D1/0231 , B60W30/17 , B60W2420/42 , G06K9/00791 , G06K9/00805 , G06K9/3241 , G06K9/6293 , G06K2209/23
Abstract: The present disclosure is directed to an autonomous vehicle having a vehicle control system. The vehicle control system includes a vehicle detection system. The vehicle detection system includes receiving an image of a field of view of the vehicle and identifying a region-pair in the image with a sliding-window filter. The region-pair is made up of a first region and a second region. Each region is determined based on a color of pixels within the sliding-window filter. The vehicle detection system also determines a potential second vehicle in the image based on the region-pair. In response to determining the potential second vehicle in the image, the vehicle detection system performs a multi-stage classification of the image to determine whether the second vehicle is present in the image. Additionally, the vehicle detection system provides instructions to control the first vehicle based at least on the determined second vehicle.
Abstract translation: 本公开涉及具有车辆控制系统的自主车辆。 车辆控制系统包括车辆检测系统。 车辆检测系统包括接收车辆的视野的图像并且利用滑动窗口过滤器识别图像中的区域对。 区域对由第一区域和第二区域构成。 基于滑动窗口滤波器内的像素的颜色来确定每个区域。 车辆检测系统还基于区域对来确定图像中的潜在的第二车辆。 响应于确定图像中的潜在的第二车辆，车辆检测系统执行图像的多级分类，以确定第二车辆是否存在于图像中。 另外，车辆检测系统至少基于所确定的第二车辆提供控制第一车辆的指令。
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公开(公告)号：US09305223B1
公开(公告)日：2016-04-05
申请号：US13927248
申请日：2013-06-26
Applicant: Google Inc.
Inventor： Abhijit Ogale , David Ian Franklin Ferguson
IPC: G06K9/00
CPC classification number: G06K9/00791 , B60R1/00 , B60R2300/80 , G05D1/0088 , G05D1/0246 , G06K9/00825 , G06K9/4604 , G06K9/4652 , G06K9/4661 , H04N5/2353
Abstract: An autonomous vehicle is configured to detect an active turn signal indicator on another vehicle. An image-capture device of the autonomous vehicle captures an image of a field of view of the autonomous vehicle. The autonomous vehicle captures the image with a short exposure to emphasize objects having brightness above a threshold. Additionally, a bounding area for a second vehicle located within the image is determined. The autonomous vehicle identifies a group of pixels within the bounding area based on a first color of the group of pixels. The autonomous vehicle also calculates an oscillation of an intensity of the group of pixels. Based on the oscillation of the intensity, the autonomous vehicle determines a likelihood that the second vehicle has a first active turn signal. Additionally, the autonomous vehicle is controlled based at least on the likelihood that the second vehicle has a first active turn signal.
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公开(公告)号：US09201424B1
公开(公告)日：2015-12-01
申请号：US14010937
申请日：2013-08-27
Applicant: Google Inc.
Inventor： Abhijit Ogale
CPC classification number: G05D1/0094 , G01C11/06 , G05D1/0253 , G05D2201/0213 , G06T7/80 , G06T2207/10016 , G06T2207/10021 , G06T2207/30244 , G06T2207/30248 , G06T2207/30252
Abstract: Example methods and systems for camera calibration using structure from motion techniques are described herein. Within examples, an autonomous vehicle may receive images from a vehicle camera system and may determine an image-based pose based on the images. To determine an image-bases pose, an autonomous vehicle may perform various processes related to structure from motion, such as image matching and bundle adjustment. In addition, the vehicle may determine a sensor-based pose indicative of a position and orientation of the vehicle through using information provided by vehicle sensors. The vehicle may align the image-based pose with the sensor-based pose to determine any adjustments to the position or orientation that may calibrate the cameras. In an example, a computing device of the vehicle may align the different poses using transforms, rotations, and/or scaling.
Abstract translation: 本文描述了使用来自运动技术的结构的用于相机校准的示例性方法和系统。 在示例中，自主车辆可以从车辆摄像机系统接收图像，并且可以基于图像来确定基于图像的姿势。 为了确定图像基础姿势，自主车辆可以执行与运动结构相关的各种处理，例如图像匹配和束调整。 此外，车辆可以通过使用由车辆传感器提供的信息来确定指示车辆的位置和方向的基于传感器的姿势。 车辆可以将基于图像的姿势与基于传感器的姿态对准，以确定对可校准相机的位置或方向的任何调整。 在一个示例中，车辆的计算设备可以使用变换，旋转和/或缩放来对准不同姿态。
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Patent Agency Ranking
公开(公告)号：US09047706B1
公开(公告)日：2015-06-02
申请号：US13801810
申请日：2013-03-13
Applicant: Google Inc.
Inventor： Abhijit Ogale
CPC classification number: G06T19/20 , G06T7/593 , G06T15/20 , G06T17/00 , G06T2200/04 , G06T2207/10028
Abstract: To align a first digital 3D model of a scene with a second digital 3D model of the scene, real-world photographs of the scene are received and synthetic photographs of the first digital 3D model are generated according to different camera poses of a virtual camera. Using the real-world photographs and the synthetic photographs as input photographs, points in a coordinate system of the second digital 3D model are generated. Camera poses of the input photographs in the coordinate system of the second 3D model also are determined. Alignment data for aligning the first 3D model with the second 3D model is generated using the camera poses of the virtual camera and the camera poses corresponding to the input photographs.
Abstract translation: 为了将场景的第一数字3D模型与场景的第二数字3D模型对准，接收场景的真实世界照片，并且根据虚拟相机的不同相机姿态来生成第一数字3D模型的综合照片。 使用真实世界照片和合成照片作为输入照片，生成第二数字3D模型的坐标系中的点。 确定在第二3D模型的坐标系中的输入照片的相机姿态。 用于使第一3D模型与第二3D模型对齐的对准数据使用虚拟摄像机的摄像头姿态和与输入照片相对应的姿势来生成。
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公开(公告)号：US20160283804A1
公开(公告)日：2016-09-29
申请号：US15173347
申请日：2016-06-03
Applicant: Google Inc.
Inventor： Vadim Furman , Andrew Hughes Chatham , Abhijit Ogale , Dmitri Dolgov
CPC classification number: G06K9/00805 , B60R11/04 , B60R2011/0026 , B60R2011/004 , B60R2011/008 , G01C21/00 , G01C21/30 , G06K9/00791 , G06K9/6202 , G06T9/00 , H04N19/117 , H04N19/136 , H04N19/167 , H04N19/17 , H04N19/85
Abstract: A vehicle may receive one or more images of an environment of the vehicle. The vehicle may also receive a map of the environment. The vehicle may also match at least one feature in the one or more images with corresponding one or more features in the map. The vehicle may also identify a given area in the one or more images that corresponds to a a portion of the map that is within a threshold distance to the one or more features. The vehicle may also compress the one or more images to include a lower amount of details in areas of the one or more images other than the given area. The vehicle may also provide the compressed images to a remote system, and responsively receive operation instructions from the remote system.
Abstract translation: 车辆可以接收车辆的环境的一个或多个图像。 车辆还可以接收环境地图。 车辆还可以将一个或多个图像中的至少一个特征与图中的相应的一个或多个特征进行匹配。 车辆还可以识别与一个或多个特征的阈值距离内的对应于地图的一部分的一个或多个图像中的给定区域。 车辆还可以压缩一个或多个图像以在除了给定区域之外的一个或多个图像的区域中包括较少量的细节。 车辆还可以将压缩图像提供给远程系统，并且响应地接收来自远程系统的操作指令。
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公开(公告)号：US20160092755A1
公开(公告)日：2016-03-31
申请号：US14883956
申请日：2015-10-15
Applicant: Google Inc.
Inventor： Nathaniel Fairfield , David Ian Ferguson , Abhijit Ogale , Matthew Wang , Yangli Hector Yee
CPC classification number: G06K9/78 , B60T1/10 , B60T7/12 , B60T7/18 , B60T7/22 , B60T2201/08 , B60W30/10 , B60W30/143 , B60W40/06 , B60W2420/42 , B60W2550/14 , B60W2550/22 , B62D6/00 , B62D15/025 , B62D15/0255 , B62D15/0265 , G01S7/4802 , G01S7/4808 , G01S13/865 , G01S13/867 , G01S13/931 , G01S17/89 , G01S17/936 , G01S2013/9353 , G01S2013/936 , G05D1/0088 , G05D1/0214 , G05D1/024 , G05D1/0246 , G05D1/0257 , G05D1/027 , G05D1/0278 , G05D2201/0213 , G06K9/00798 , G06K9/00805 , G06K9/00818 , H04N7/18
Abstract: Methods and systems for detection of a construction zone sign are described. A computing device, configured to control the vehicle, may be configured to receive, from an image-capture device coupled to the computing device, images of a vicinity of the road on which the vehicle is travelling. Also, the computing device may be configured to determine image portions in the images that may depict sides of the road at a predetermined height range. Further, the computing device may be configured to detect a construction zone sign in the image portions, and determine a type of the construction zone sign. Accordingly, the computing device may be configured to modify a control strategy associated with a driving behavior of the vehicle; and control the vehicle based on the modified control strategy.
Abstract translation: 描述了用于检测结构区域符号的方法和系统。 被配置为控制车辆的计算设备可以被配置为从耦合到计算设备的图像捕获设备接收车辆行驶的道路附近的图像。 此外，计算设备可以被配置为确定可以在预定高度范围处描绘道路的侧面的图像中的图像部分。 此外，计算装置可以被配置为检测图像部分中的构造区域标记，并且确定构造区域符号的类型。 因此，计算设备可以被配置为修改与车辆的驾驶行为相关联的控制策略; 并根据修改的控制策略控制车辆。
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18.发明授权公开(公告)号：US09286520B1
公开(公告)日：2016-03-15
申请号：US13942747
申请日：2013-07-16
Applicant: Google Inc.
Inventor： Wan-Yen Lo , David Ian Franklin Ferguson , Abhijit Ogale
CPC classification number: G06K9/00798 , B60R1/00 , G06K9/00791 , G06K9/00805 , G06K9/00845 , G06K9/4647 , G06K9/4652 , G06K9/52 , G06K9/6215 , G06K2009/4666 , G06T7/20 , G06T7/408 , G06T2207/30256
Abstract: Methods and systems for real-time road flare detection using templates and appropriate color spaces are described. A computing device of a vehicle may be configured to receive an image of an environment of the vehicle. The computing device may be configured to identify a given pixels in the plurality of pixels having one or more of: (i) a red color value greater than a green color value, and (ii) the red color value greater than a blue color value. Further, the computing device may be configured to make a comparison between one or more characteristics of a shape of an object represented by the given pixels in the image and corresponding one or more characteristics of a predetermined shape of a road flare; and determine a likelihood that the object represents the road flare.
Abstract translation: 描述了使用模板和适当颜色空间进行实时道路耀斑检测的方法和系统。 车辆的计算装置可以被配置为接收车辆的环境的图像。 计算设备可以被配置为识别具有以下中的一个或多个的多个像素中的给定像素：（i）大于绿色值的红色值，以及（ii）大于蓝色值的红色值 。 此外，计算装置可以被配置为对由图像中的给定像素表示的对象的形状的一个或多个特征与道路耀斑的预定形状的相应一个或多个特征进行比较; 并确定对象表示道路耀斑的可能性。
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公开(公告)号：US09164511B1
公开(公告)日：2015-10-20
申请号：US13864336
申请日：2013-04-17
Applicant: Google Inc.
Inventor： Dave Ferguson , Abhijit Ogale
IPC: G05D1/02
CPC classification number: G05D1/0088 , B60W30/00 , G01S13/02 , G01S17/02 , G01S19/13 , G05D1/0231 , G05D1/0246 , G05D2201/0213 , G06K9/00805 , G06K9/00825
Abstract: Methods and systems for the use of detected objects for image processing are described. A computing device autonomously controlling a vehicle may receive images of the environment surrounding the vehicle from an image-capture device coupled to the vehicle. In order to process the images, the computing device may receive information indicating characteristics of objects in the images from one or more sources coupled to the vehicle. Examples of sources may include RADAR, LIDAR, a map, sensors, a global positioning system (GPS), or other cameras. The computing device may use the information indicating characteristics of the objects to process received images, including determining the approximate locations of objects within the images. Further, while processing the image, the computing device may use information from sources to determine portions of the image to focus upon that may allow the computing device to determine a control strategy based on portions of the image.
Abstract translation: 描述了使用检测对象进行图像处理的方法和系统。 自动控制车辆的计算设备可以从耦合到车辆的图像捕获设备接收车辆周围环境的图像。 为了处理图像，计算设备可以接收指示来自耦合到车辆的一个或多个源的图像中的对象的特征的信息。 源的示例可以包括RADAR，LIDAR，地图，传感器，全球定位系统（GPS）或其他相机。 计算设备可以使用指示对象的特征的信息来处理接收到的图像，包括确定图像内的对象的大致位置。 此外，在处理图像的同时，计算设备可以使用来自源的信息来确定图像焦点的部分，从而允许计算设备基于图像的部分来确定控制策略。
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