US 12,277,721 B2
Method for optimizing depth estimation model, computer device, and storage medium
Tsung-Wei Liu, New Taipei (TW); and Chin-Pin Kuo, New Taipei (TW)
Assigned to HON HAI PRECISION INDUSTRY CO., LTD., New Taipei (TW)
Filed by HON HAI PRECISION INDUSTRY CO., LTD., New Taipei (TW)
Filed on Aug. 26, 2022, as Appl. No. 17/896,835.
Claims priority of application No. 202210616086.5 (CN), filed on May 31, 2022.
Prior Publication US 2023/0410338 A1, Dec. 21, 2023
Int. Cl. G06V 10/776 (2022.01); G01S 13/86 (2006.01); G06T 7/55 (2017.01); G06T 7/73 (2017.01)
CPC G06T 7/55 (2017.01) [G01S 13/867 (2013.01); G06T 7/74 (2017.01); G06V 10/776 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30244 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for optimizing a depth estimation model applied to a computer device, the method comprising:
obtaining a video of an object and capturing a first image and a second image from the video;
obtaining an initial depth estimation model, and obtaining an updated depth estimation model by performing an optimization process on the initial depth estimation model; and
repeatedly performing the optimization process on the updated depth estimation model until the updated depth estimation model meets predetermined requirements, and determining the updated depth estimation model that meets the predetermined requirements as a target depth estimation model;
wherein the optimization process on the initial depth estimation model comprises:
obtaining a first depth image of the first image by using the initial depth estimation model;
obtaining a correspondence between each pixel point in the first image and each pixel point in the second image;
obtaining a third image by performing a back projection on the first depth image;
obtaining a fourth image by updating a pixel value of each pixel point in the third image to be a pixel value of the corresponding pixel point in the second image according to the correspondence between each pixel point in the first image and each pixel point in the second image;
obtaining an initial loss function between the first image and the fourth image based on the initial depth estimation model;
obtaining a depth value of each pixel point in the first image and the fourth image by using a radar device, and obtaining an updated loss function by optimizing the initial loss function based on the depth value; and
obtaining the updated depth estimation model by optimizing the initial depth estimation model using the updated loss function.