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Computer Science > Computer Vision and Pattern Recognition

arXiv:2105.10831 (cs)
[Submitted on 23 May 2021]

Title:Stereo Matching Based on Visual Sensitive Information

Authors:Hewei Wang, Muhammad Salman Pathan, Soumyabrata Dev
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Abstract:The area of computer vision is one of the most discussed topics amongst many scholars, and stereo matching is its most important sub fields. After the parallax map is transformed into a depth map, it can be applied to many intelligent fields. In this paper, a stereo matching algorithm based on visual sensitive information is proposed by using standard images from Middlebury dataset. Aiming at the limitation of traditional stereo matching algorithms regarding the cost window, a cost aggregation algorithm based on the dynamic window is proposed, and the disparity image is optimized by using left and right consistency detection to further reduce the error matching rate. The experimental results show that the proposed algorithm can effectively enhance the stereo matching effect of the image providing significant improvement in accuracy as compared with the classical census algorithm. The proposed model code, dataset, and experimental results are available at this https URL.
Comments: Published in 6th IEEE International Conference on Image, Vision and Computing (ICIVC), 2021
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2105.10831 [cs.CV]
  (or arXiv:2105.10831v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2105.10831

Submission history

From: Soumyabrata Dev [view email]
[v1] Sun, 23 May 2021 00:20:32 UTC (433 KB)
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