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公开(公告)号：US10395126B2
公开(公告)日：2019-08-27
申请号：US14822951
申请日：2015-08-11
发明人： Yan Lu , Aniket Murarka , Kikuo Fujimura , Ananth Ranganathan
摘要： Systems and techniques for sign based localization are provided herein. Sign based localization may be achieved by capturing an image of an operating environment around a vehicle, extracting one or more text candidates from the image, detecting one or more line segments within the image, defining one or more quadrilateral candidates based on one or more of the text candidates, one or more of the line segments, and one or more intersections of respective line segments, determining one or more sign candidates for the image based on one or more of the quadrilateral candidates and one or more of the text candidates, matching one or more of the sign candidates against one or more reference images, and determining a location of the vehicle based on a match between one or more of the sign candidates and one or more of the reference images.
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公开(公告)号：US10282860B2
公开(公告)日：2019-05-07
申请号：US15601638
申请日：2017-05-22
发明人： Yan Lu , Jiawei Huang , Yi-Ting Chen , Bernd Heisele
摘要： The present disclosure relates to methods and systems for monocular localization in urban environments. The method may generate an image from a camera at a pose. The method may receive a pre-generated map, and determine features from the generated image based on edge detection. The method may predict a pose of the camera based on at least the pre-generated map, and determine features from the predicted camera pose. Further, the method may determine a Chamfer distance based upon the determined features from the image and the predicted camera pose, optimize the determined Chamfer distance based upon odometry information and epipolar geometry. Upon optimization, the method may determine an estimated camera pose.
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公开(公告)号：US10997746B2
公开(公告)日：2021-05-04
申请号：US16381373
申请日：2019-04-11
摘要： Feature descriptor matching described herein may include receiving a first input image and a second input image. A feature detector may detect features from the first and second input images. A descriptor extractor may learn local feature descriptors from the features of the first and second input images based on a feature descriptor matching model trained using a ground truth data set. The descriptor extractor may determine a listwise mean average precision (mAP) rank of a pool of candidate image patches from the second input image with respect to a queried image patch from the first input image based on the feature descriptor matching model, the first set of local feature descriptors, and the second set of local feature descriptors. The descriptor matcher may generate a geometric transformation between the first input image and the second input image based on the listwise mAP and a convolutional neural network.
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公开(公告)号：US20190318502A1
公开(公告)日：2019-10-17
申请号：US16381373
申请日：2019-04-11
摘要： Feature descriptor matching described herein may include receiving a first input image and a second input image. A feature detector may detect features from the first and second input images. A descriptor extractor may learn local feature descriptors from the features of the first and second input images based on a feature descriptor matching model trained using a ground truth data set. The descriptor extractor may determine a listwise mean average precision (mAP) rank of a pool of candidate image patches from the second input image with respect to a queried image patch from the first input image based on the feature descriptor matching model, the first set of local feature descriptors, and the second set of local feature descriptors. The descriptor matcher may generate a geometric transformation between the first input image and the second input image based on the listwise mAP and a convolutional neural network.
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公开(公告)号：US20170046580A1
公开(公告)日：2017-02-16
申请号：US14822951
申请日：2015-08-11
申请人： Honda Motor Co., Ltd
发明人： Yan Lu , Aniket Murarka , Kikuo Fujimura , Ananth Ranganathan
CPC分类号： G06K9/00818 , G06K9/4671 , G06K2009/363 , G06T7/74 , G06T2207/30244 , G06T2207/30252 , H04N7/181 , H04N7/185
摘要： Systems and techniques for sign based localization are provided herein. Sign based localization may be achieved by capturing an image of an operating environment around a vehicle, extracting one or more text candidates from the image, detecting one or more line segments within the image, defining one or more quadrilateral candidates based on one or more of the text candidates, one or more of the line segments, and one or more intersections of respective line segments, determining one or more sign candidates for the image based on one or more of the quadrilateral candidates and one or more of the text candidates, matching one or more of the sign candidates against one or more reference images, and determining a location of the vehicle based on a match between one or more of the sign candidates and one or more of the reference images.
摘要翻译： 本文提供了基于符号定位的系统和技术。 基于符号的定位可以通过捕获车辆周围的操作环境的图像来实现，从图像中提取一个或多个文本候选，检测图像内的一个或多个线段，基于以下中的一个或多个来定义一个或多个四边形候选 文本候选者，线段中的一个或多个以及各个线段的一个或多个交叉点，基于一个或多个四边形候选和一个或多个文本候选来确定图像的一个或多个符号候选，匹配 一个或多个符号候选者针对一个或多个参考图像，以及基于一个或多个符号候选物和一个或多个参考图像之间的匹配来确定车辆的位置。
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