Multiple data cost-based stereo matching method to generate dense disparity maps from images under radiometric variations

Shetty, Akhil Appu and George, V I and Nayak, Gurudas C (2020) Multiple data cost-based stereo matching method to generate dense disparity maps from images under radiometric variations. International Journal of Intelligent Systems Technologies and Applications, 19 (4). pp. 393-404. ISSN 1740-8865

[img] PDF
10389.pdf - Published Version
Restricted to Registered users only

Download (1MB) | Request a copy

Abstract

Stereo matching algorithms are capable of providing dense 3D information of the environment through two images taken simultaneously from a pair of cameras placed parallel to each other. Obtaining an accurate disparity map from a stereo image pair is a challenging task and also computationally expensive. If we take into consideration the environmental effect, then the difficulty of the task increases drastically. The authors try to overcome this problem by combining multiple stereo cost functions in the form of a linear equation. To reduce the computation time, a segmentation based cost aggregation method is followed in an attempt to produce an accurate disparity map even in the presence of radiometric variations in the images. The performance of the proposed algorithm is observed while varying the parameter ‘’ between the cost functions and the number of segments in the images. Different image pairs from the Middlebury stereo dataset were considered her

Item Type: Article
Uncontrolled Keywords: stereo matching; Middlebury stereo dataset; SLIC segmentation; disparity map
Subjects: Engineering > MIT Manipal > Instrumentation and Control
Engineering > MIT Manipal > Mechanical and Manufacturing
Depositing User: MIT Library
Date Deposited: 12 Jan 2021 09:12
Last Modified: 12 Jan 2021 09:12
URI: http://eprints.manipal.edu/id/eprint/156199

Actions (login required)

View Item View Item