US 12,112,552 B2
Lane marker recognition
Seungwoo Yoo, Yongin-si (KR); Heesoo Myeong, Seoul (KR); and Hee-Seok Lee, Seongnam-si (KR)
Assigned to QUALCOMM Incorporated, San Diego, CA (US)
Filed by QUALCOMM Incorporated, San Diego, CA (US)
Filed on Mar. 18, 2022, as Appl. No. 17/655,500.
Prior Publication US 2023/0298360 A1, Sep. 21, 2023
Int. Cl. G06V 20/56 (2022.01); G06T 7/73 (2017.01); G06V 10/82 (2022.01)
CPC G06V 20/588 (2022.01) [G06T 7/73 (2017.01); G06V 10/82 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30256 (2013.01)] 30 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
generating a set of feature tensors by processing an input image using a convolutional neural network;
generating a set of localizations by processing the set of feature tensors using a localization network;
generating a set of horizontal positions by processing the set of feature tensors using row-wise regression;
generating a set of end positions by processing the set of feature tensors using y-end regression; and
determining a set of lane marker positions based on the set of localizations, the set of horizontal positions, and the set of end positions.