US 12,450,869 B2
Method of processing image, method of training model, and electronic device
Yuzhe He, Beijing (CN); Yao Zhou, Beijing (CN); Shenhua Hou, Beijing (CN); Liang Peng, Beijing (CN); and Guowei Wan, Beijing (CN)
Assigned to APOLLO INTELLIGENT DRIVING TECHNOLOGY (BEIJING) CO., LTD., Beijing (CN)
Filed by Apollo Intelligent Driving Technology (Beijing) Co., Ltd., Beijing (CN)
Filed on Dec. 28, 2022, as Appl. No. 18/089,709.
Claims priority of application No. 202111635804.5 (CN), filed on Dec. 29, 2021.
Prior Publication US 2023/0162474 A1, May 25, 2023
Int. Cl. G06V 10/75 (2022.01); G06T 7/73 (2017.01); G06V 10/46 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/80 (2022.01)
CPC G06V 10/757 (2022.01) [G06T 7/74 (2017.01); G06V 10/46 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01); G06V 10/806 (2022.01); G06T 2207/20081 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A method of processing an image, comprising:
processing a to-be-processed image to obtain a feature point of the to-be-processed image, a feature point descriptor map of the to-be-processed image, and a dense descriptor map of the to-be-processed image;
determining a pair of matched feature points between the to-be-processed image and a reference image, based on the feature point and the feature point descriptor map; and
determining a pair of matched pixels between the to-be-processed image and the reference image, based on the dense descriptor map,
wherein the processing a to-be-processed image to obtain a feature point of the to-be-processed image, a feature point descriptor map of the to-be-processed image and a dense descriptor map of the to-be-processed image comprises:
inputting the to-be-processed image into a multi-task processing model to obtain the feature point of the to-be-processed image, the feature point descriptor map of the to-be-processed image and the dense descriptor map of the to-be-processed image,
wherein the multi-task processing model comprises a feature point classification branch, and the method further comprises:
inputting the to-be-processed image into the feature point classification branch to obtain a feature point category result, so as to determine the pair of matched feature points between the to-be-processed image and the reference image based on the feature point, the feature point descriptor map and the feature point category result,
wherein the determining a pair of matched feature points between the to-be-processed image and a reference image based on the feature point and the feature point descriptor map comprises:
screening the feature point based on the feature point category result, so as to determine a target feature point; and
determining the pair of matched feature points between the to-be-processed image and the reference image based on the target feature point and the feature point descriptor map, and
wherein the determining the pair of matched feature points between the to-be-processed image and the reference image based on the target feature point and the feature point descriptor map comprises:
extracting, from the feature point descriptor map, a feature point descriptor matched with the target feature point based on the target feature point; and
determining, by using a feature point matching method, the pair of matched feature points between the to-be-processed image and the reference image based on the target feature point and the feature point descriptor matched with the target feature point.