The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jul. 09, 2024
Filed:
Feb. 23, 2022
Beijing Tusen Zhitu Technology Co., Ltd., Beijing, CN;
Naiyan Wang, Beijing, CN;
Yuanqin Lu, Beijing, CN;
BEIJING TUSEN ZHITU TECHNOLOGY CO., LTD., Beijing, CN;
Abstract
The present disclosure provides a method and an apparatus for binocular ranging, capable of achieving an improved accuracy of binocular ranging. The method includes: extracting features from a left image and a right image to obtain a left feature image and a right feature image; selecting a standard feature image and obtaining a cost volume of the standard feature image by applying a correlation calculation to the left feature image and the right feature image using a block matching algorithm; obtaining a confidence volume by normalizing computational costs of all disparity values in a disparity dimension for each pixel point in the cost volume; obtaining a confidence map by selecting a maximum value from confidence levels of all the disparity values in the disparity dimension for each pixel point in the confidence volume; obtaining a mask map by mapping each pixel point having a confidence level higher than a predetermined threshold in the confidence map to 1 and mapping each pixel point having a confidence level lower than or equal to the threshold in the confidence map to 0; obtaining a disparity map by calculating an argmax value for the confidence levels of all disparity values in the disparity dimension for each pixel point in the confidence volume; obtaining a target disparity map by multiplying the mask map with the disparity map; and estimating a distance based on the target disparity map.