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公开(公告)号：US20200218909A1
公开(公告)日：2020-07-09
申请号：US16733228
申请日：2020-01-02
Applicant: QUALCOMM Incorporated
Inventor： Heesoo MYEONG , Hee-Seok LEE , Duck Hoon KIM , Seungwoo YOO , Kang KIM
IPC: G06K9/00
Abstract: Disclosed are techniques for performing lane instance recognition. Lane instances are difficult to recognize since they are long and elongated, and they also look different from view to view. An approach is proposed in which local mask segmentation lane estimation and global control points lane estimation are combined.
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公开(公告)号：US20210287018A1
公开(公告)日：2021-09-16
申请号：US17200592
申请日：2021-03-12
Applicant: QUALCOMM Incorporated
Inventor： Seungwoo YOO , Heesoo MYEONG , Hee-Seok LEE
Abstract: Certain aspects of the present disclosure provide a method for lane marker detection, including: receiving an input image; providing the input image to a lane marker detection model; processing the input image with a shared lane marker portion of the lane marker detection model; processing output of the shared lane marker portion of the lane marker detection model with a plurality of lane marker-specific representation layers of the lane marker detection model to generate a plurality of lane marker representations; and outputting a plurality of lane markers based on the plurality of lane marker representations.
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Patent Agency Ranking
公开(公告)号：US20210192231A1
公开(公告)日：2021-06-24
申请号：US16723925
申请日：2019-12-20
Applicant: QUALCOMM Incorporated
Inventor： Hee-Seok LEE , Heesoo MYEONG , Hankyu CHO
Abstract: Autonomous driving systems described herein provide an efficient way to manage camera-based perception by considering the characteristics of captured images. In one example, a camera sensor may capture an image and a processor may determine a first region of interest (ROI) within the image and a second ROI within the image. The processor may generate a first image of the first ROI and a second image of the second ROI. The processor may transmit a control signal based on one or more objects detected in the first ROI and/or one or more objects detected in the second ROI to cause the vehicle to perform an autonomous driving operation.
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公开(公告)号：US20200219316A1
公开(公告)日：2020-07-09
申请号：US16733234
申请日：2020-01-02
Applicant: QUALCOMM Incorporated
Inventor： Young-Ki BAIK , Hyun-Mook CHO , Duck Hoon KIM , Jeong-Kyun LEE , ChaeSeong LIM , Hee-Seok LEE
Abstract: Disclosed are techniques for estimating a 3D bounding box (3DBB) from a 2D bounding box (2DBB). Conventional techniques to estimate 3DBB from 2DBB rely upon classifying target vehicles within the 2DBB. When the target vehicle is misclassified, the projected bounding box from the estimated 3DBB is inaccurate. To address such issues, it is proposed to estimate the 3DBB without relying upon classifying the target vehicle.
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公开(公告)号：US20230298360A1
公开(公告)日：2023-09-21
申请号：US17655500
申请日：2022-03-18
Applicant: QUALCOMM Incorporated
Inventor： Seungwoo YOO , Heesoo MYEONG , Hee-Seok LEE
CPC classification number: G06V20/588 , G06V10/82 , G06T7/73 , G06T2207/20081 , G06T2207/20084 , G06T2207/30256
Abstract: Certain aspects of the present disclosure provide techniques for lane marker detection. A set of feature tensors is generated by processing an input image using a convolutional neural network. A set of localizations is generated by processing the set of feature tensors using a localization network, a set of horizontal positions is generated by processing the set of feature tensors using row-wise regression, and a set of end positions is generated by processing the set of feature tensors using y-end regression. A set of lane marker positions is determined based on the set of localizations, the set of horizontal positions, and the set of end positions.
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公开(公告)号：US20230112799A1
公开(公告)日：2023-04-13
申请号：US18047538
申请日：2022-10-18
Applicant: QUALCOMM Incorporated
Inventor： Young-Ki BAIK , Hyun-Mook CHO , Duck Hoon KIM , Jeong-Kyun LEE , Chaeseong LIM , Hee-Seok LEE
Abstract: Disclosed are techniques for estimating a 3D bounding box (3DBB) from a 2D bounding box (2DBB). Conventional techniques to estimate 3DBB from 2DBB rely upon classifying target vehicles within the 2DBB. When the target vehicle is misclassified, the projected bounding box from the estimated 3DBB is inaccurate. To address such issues, it is proposed to estimate the 3DBB without relying upon classifying the target vehicle.
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公开(公告)号：US20180189580A1
公开(公告)日：2018-07-05
申请号：US15441114
申请日：2017-02-23
Applicant: QUALCOMM Incorporated
Inventor： Hee-Seok LEE , Duck Hoon KIM
CPC classification number: G06K9/00818 , G06K9/4604 , G06K9/4628 , G06K9/627 , G06T7/13 , G06T7/168 , G06T7/50 , G06T2207/20084 , G06T2207/30252
Abstract: A method, a computer-readable medium, and an apparatus for object detection are provided. The apparatus may determine a regression vector using a neural network based on an input image that contains an object. The object may have a planar surface with a known shape. The apparatus may derive a transform matrix based on the regression vector. The apparatus may identify a precise boundary of the object based on the transform matrix. The precise boundary of the object may include a plurality of vertices of the object. To identify the boundary of the object, the apparatus may apply the transform matrix to a determined shape of the object.
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