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

IPC: G06K9/00 ,  G06T7/73 ,  G06T7/10

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.

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.

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

IPC: G06V20/56 ,  G06V10/82 ,  G06T7/73

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.

公开(公告)号：US20200218908A1

公开(公告)日：2020-07-09

申请号：US16733148

申请日：2020-01-02

Applicant: QUALCOMM Incorporated

Inventor： Jeong-Kyun LEE ,  Young-Ki BAIK ,  Seungwoo YOO ,  Duck Hoon KIM

IPC: G06K9/00 ,  G06K9/46 ,  G06K9/62

Abstract: Disclosed are techniques for estimating multiple lane boundaries through simultaneous detection of lane markers (LM) and raised pavement markers (RPM). Conventional techniques for lane marker detection (LMD) comprises extracting and clustering line segments from a camera image, fitting the clustered lines to a geometric model, and selecting the multiple lanes using heuristic approaches. Unfortunately, in the conventional technique, an error from each step is sequentially propagated to the next step. Also there are no techniques to estimate both LMs and RPMs. A technique to simultaneously detect in real time both LM and RPMs is proposed. This enables optimal estimation of multiple lane boundaries.