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Patent Agency Ranking
公开(公告)号：US10102644B2
公开(公告)日：2018-10-16
申请号：US15384615
申请日：2016-12-20
Applicant: Delphi Technologies, Inc.
Inventor： Jens Westerhoff , Stephanie Lessmann , Mirko Meuter , Jan Siegemund
Abstract: A method of estimating an orientation of a camera relative to a surface includes providing a first image and a subsequent second image captured by the camera; selecting a first point from the first image and a second point from the second image, where the first and second points represent the same object; defining a first optical flow vector connecting the first point and the second point; carrying out a first estimation step comprising estimating two components of the normal vector in the camera coordinate system by using the first optical flow vector and restricting parameter space to only the two components of the normal vector, wherein a linear equation system derived from a homography matrix that represents a projective transformation between the first image and the second image is provided and the two components of the normal vector in the camera coordinate system are estimated by solving the linear equation system; and determining the orientation of the camera relative to the surface using the results of the first estimation step.
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2.发明申请公开(公告)号：US20170206674A1
公开(公告)日：2017-07-20
申请号：US15384615
申请日：2016-12-20
Applicant: Delphi Technologies, Inc.
Inventor： Jens Westerhoff , Stephanie Lessmann , Mirko Meuter , Jan Siegemund
CPC classification number: G06T7/70 , B60R11/04 , G06T3/20 , G06T7/60 , G06T7/97 , G06T2207/30244 , G06T2207/30252
Abstract: A method of estimating an orientation of a camera relative to a surface includes providing a first image and a subsequent second image captured by the camera; selecting a first point from the first image and a second point from the second image, where the first and second points represent the same object; defining a first optical flow vector connecting the first point and the second point; carrying out a first estimation step comprising estimating two components of the normal vector in the camera coordinate system by using the first optical flow vector and restricting parameter space to only the two components of the normal vector, wherein a linear equation system derived from a homography matrix that represents a projective transformation between the first image and the second image is provided and the two components of the normal vector in the camera coordinate system are estimated by solving the linear equation system; and determining the orientation of the camera relative to the surface using the results of the first estimation step.
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3.发明授权公开(公告)号：US09862318B2
公开(公告)日：2018-01-09
申请号：US14953848
申请日：2015-11-30
Applicant: Delphi Technologies, Inc.
Inventor： Stephanie Lessmann , Mirko Meuter , Dennis Mueller
CPC classification number: B60R1/00 , B60R2300/8033 , B60R2300/804 , G06K9/00805 , G06K9/3241 , G06K9/6278 , G06T7/246 , G06T7/73 , H04N5/225
Abstract: A method of determining the distance of an object from an automated vehicle based on images taken by a monocular image acquiring device. The object is recognized with an object-class by means of an image processing system. Respective position data are determined from the images using a pinhole camera model based on the object-class. Position data indicating in world coordinates the position of a reference point of the object with respect to the plane of the road is used with a scaling factor of the pinhole camera model estimated by means of a Bayes estimator using the position data as observations and under the assumption that the reference point of the object is located on the plane of the road with a predefined probability. The distance of the object from the automated vehicle is calculated from the estimated scaling factor using the pinhole camera model.
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公开(公告)号：US20170278014A1
公开(公告)日：2017-09-28
申请号：US15467684
申请日：2017-03-23
Applicant: Delphi Technologies, Inc.
Inventor： Stephanie Lessmann , Mirko Meuter , Jens Westerhoff
CPC classification number: G06N20/00 , G06K9/00791 , G06K9/6262 , G06K9/6267 , G06K9/66 , G06T5/20 , G06T7/269 , G06T7/73 , G06T2207/10016 , G06T2207/20081 , G06T2207/30244 , G06T2207/30252
Abstract: A method of generating a confidence measure for an estimation derived from images captured by a camera mounted on a vehicle includes: capturing consecutive training images by the camera while the vehicle is moving; determining ground-truth data for the training images; computing optical flow vectors from the training images and estimating a first output signal based on the optical flow vectors for each of the training images, the first output signal indicating an orientation of the camera; classifying the first output signal for each of the training images as a correct signal or a false signal depending on how good the first output signal fits to the ground-truth data; determining optical flow field properties for each of the training images derived from the training images; and generating a separation function that separates the optical flow field properties into two classes based on the classification of the first output signal.
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5.发明申请Method To Determine Distance Of An Object From An Automated Vehicle With A Monocular Device 有权用于确定来自具有单眼装置的自动车辆的物体的距离的方法公开(公告)号：US20160180531A1
公开(公告)日：2016-06-23
申请号：US14953848
申请日：2015-11-30
Applicant: Delphi Technologies, Inc.
Inventor： Stephanie Lessmann , Mirko Meuter , Dennis Mueller
CPC classification number: B60R1/00 , B60R2300/8033 , B60R2300/804 , G06K9/00805 , G06K9/3241 , G06K9/6278 , G06T7/246 , G06T7/73 , H04N5/225
Abstract: A method of determining the distance of an object from an automated vehicle based on images taken by a monocular image acquiring device. The object is recognized with an object-class by means of an image processing system. Respective position data are determined from the images using a pinhole camera model based on the object-class. Position data indicating in world coordinates the position of a reference point of the object with respect to the plane of the road is used with a scaling factor of the pinhole camera model estimated by means of a Bayes estimator using the position data as observations and under the assumption that the reference point of the object is located on the plane of the road with a predefined probability. The distance of the object from the automated vehicle is calculated from the estimated scaling factor using the pinhole camera model.
Abstract translation: 根据单眼图像获取装置拍摄的图像确定物体与自动车辆的距离的方法。 通过图像处理系统用对象类识别对象。 使用基于对象类的针孔相机模型从图像确定相应的位置数据。 使用以世界坐标表示对象相对于道路平面的参考点的位置的位置数据，其中使用通过使用位置数据作为观测值的Bayes估计器估计的针孔相机模型的缩放因子，并且在 假设对象的参考点以预定的概率位于道路的平面上。 使用针孔照相机模型，根据估计的比例因子计算物体与自动车辆的距离。
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