Stereo matching algorithm based on deep learning: a survey

The development of stereo matching algorithm is still one of the challenging problems, especially in ill-posed regions. Hence, this article presents a survey on the algorithm frameworks related to the stereo matching algorithm. Based on the early survey that had been conducted, two major frameworks...

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Main Authors: Hamzah, Rostam Affendi, Hamid, Mohd Saad, Kadmin, Ahmad Fauzan, Abd Manap, Nurulfajar
Format: Article
Language:English
Published: Elsevier B.V. 2022
Online Access:http://eprints.utem.edu.my/id/eprint/26769/2/1-S2.0-S1319157820304493-MAIN.PDF
http://eprints.utem.edu.my/id/eprint/26769/
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spelling my.utem.eprints.267692023-04-14T14:53:09Z http://eprints.utem.edu.my/id/eprint/26769/ Stereo matching algorithm based on deep learning: a survey Hamzah, Rostam Affendi Hamid, Mohd Saad Kadmin, Ahmad Fauzan Abd Manap, Nurulfajar The development of stereo matching algorithm is still one of the challenging problems, especially in ill-posed regions. Hence, this article presents a survey on the algorithm frameworks related to the stereo matching algorithm. Based on the early survey that had been conducted, two major frameworks available in current stereo matching algorithm development, they are traditional and artificial intelligence (AI) frameworks. Most of the traditional methods are very low accuracy compared to the AI-based approach. This can be observed in the standard benchmarking dataset, such as from the KITTI and the Middlebury, where AI methods rank at the top of the accuracy list. Additionally, the trend for solving computer vision problems uses AI or machine learning tools that become more apparent in recent years. Thus, this paper is focusing on the survey between the deep learning frameworks, which is one of the machine learning tools related to the convolutional neural network (CNN). Several mixed approaches between CNN based method and traditional handcraft method, as well as the end to end CNN method also discussed in this paper. Elsevier B.V. 2022-05 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/26769/2/1-S2.0-S1319157820304493-MAIN.PDF Hamzah, Rostam Affendi and Hamid, Mohd Saad and Kadmin, Ahmad Fauzan and Abd Manap, Nurulfajar (2022) Stereo matching algorithm based on deep learning: a survey. Journal of King Saud University – Computer and Information Sciences, 34 (5). pp. 1663-1673. ISSN 1319-1578 https://pdf.sciencedirectassets.com/280416/1-s2.0-S1319157822X00050/1-s2.0-S1319157820304493/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEGAaCXVzLWVhc3QtMSJIMEYCIQCoMpGOpn67LJA8QZl8o9sg38kfVmIxN9gR9qf6Xw1NdgIhAJEi2MAds7N5fh3OXI2brex4jyJfl9EdSiucYh6%2F309SKrMFCDgQBRoMMDU5MDAzNTQ2ODY1Igz6eZrIAHiLV1x8vxkqkAUdWydsjUmDFTM1VUgW3jYCmXWjjGIzjrBB6OJ1rvdflaPYzgpdrTTE8C%2F7cO361Kx4753ekBwhqM2NClJyMf4VfU%2Ff7Y8Etdz5xFtSuGEkWiEiVqZt956Ho8kxbM8AmQikUp7N5ahHCwciSUEweAyT%2Fz1KhUJk2ZwfeRkPskxSSCD4mOqHoCvGn35jG1M8ALsysQVOPIuWBmqqwPXLa%2Bye0K1TGPR6J9%2FlSatDBqaOnqVoGdQKEq9Q3zoJJKgJp7l1cNl70UxPGMQ5O8dvcmmW3jJ3KaEmE66c%2BjnSmCiBFGtQSG%2FLw6lHvNXNTs8TqMyru3g9iLnPV5oFsh7%2FAYTAubLVLf5z6Pz7WhwoW27GJpWne6lyxzGOuleHjWFeWYH3XpFz936gEdXZIDuiKsO5Np7k3YIHtzehP4%2Ffh2nKVGtHjEteijE3etLJzzhMe4mHqxlX689Ft5rOC55W30EXptpvI8W3sdP0Nk4mwN4Z00NhbMHQmV%2BicAS4CpqDGOLmRKr0Hn0iLesy5o1LbIZb0X41CpNSilfL0jOIqdJK%2Br5%2F9h6vs9nQNd8UkSorgeFMFksvHGCQ7oBbqHp8TgTCA6YVVP%2BUYlt7AriTBQVDkMC%2F0A074qiA256uoCw%2BygM9drsHh0Cd3Cnl2LayGrQ4VM1i%2BfEbfWgNHDVG47oJvWshNiXHD%2FUgfrhP5YnqxJKWx653gCKbDcupwtwZufXdlO8uVJU8eXhvCZjz3RyTd379Iulz%2B28EayNeVk%2Bb41E3sLDky6FCeW0jlrrz%2BsqdQWrIuZolXBaI402LWIIyb%2BqlBJ9eG1tX11zhFl3o8M2dJ%2BZFyecrMxGDjvxkYhj8N3PiQ4dbWoKXCngOBbNBdTDax4ihBjqwAaKmzzLu2tWxh2AEKxmRugH3N06ygxYYbShvRPQ3nDlmogoDdxZKAv44Y7r%2B5fa4wGyK3p12zaYkaarsFIOP2pvqZSsXWSY9mhNUkaFPs7IybIuJE9u9BjQUSIOtSiJ4u8Ktvwj1IhttfPRb5OPS27GLEuodqZ0Xemc7aATxTPwA9rXXrqCmG3L2WoHM7oPW8rHUlNFc2e5EtgGSpMp8l0%2FeLNtqtWaN4Md9yfGNxQDu&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230328T002149Z&X-Amz-SignedHeaders=host&X-Amz-Expires=300&X-Amz-Credential=ASIAQ3PHCVTYYFHAKWNP%2F20230328%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=2a6ac841c93db2dfe4ef08b621bd37eaab1f718af2619502f6e6a191ad41c10a&hash=f51783aacbb2fcef8a7cf9ce33e26b38b5c26489d7b1519977d906ed7cfc1e83&host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&pii=S1319157820304493&tid=spdf-9fe185be-b2d9-4db3-8364-a6f1d96ad53a&sid=6fec32df1b9942425d69d7658b4f72ededf3gxrqb&type=client&tsoh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&ua=0b1a5902010506555456&rr=7aebb7179da441fc&cc=my 10.1016/j.jksuci.2020.08.011
institution Universiti Teknikal Malaysia Melaka
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country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
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language English
description The development of stereo matching algorithm is still one of the challenging problems, especially in ill-posed regions. Hence, this article presents a survey on the algorithm frameworks related to the stereo matching algorithm. Based on the early survey that had been conducted, two major frameworks available in current stereo matching algorithm development, they are traditional and artificial intelligence (AI) frameworks. Most of the traditional methods are very low accuracy compared to the AI-based approach. This can be observed in the standard benchmarking dataset, such as from the KITTI and the Middlebury, where AI methods rank at the top of the accuracy list. Additionally, the trend for solving computer vision problems uses AI or machine learning tools that become more apparent in recent years. Thus, this paper is focusing on the survey between the deep learning frameworks, which is one of the machine learning tools related to the convolutional neural network (CNN). Several mixed approaches between CNN based method and traditional handcraft method, as well as the end to end CNN method also discussed in this paper.
format Article
author Hamzah, Rostam Affendi
Hamid, Mohd Saad
Kadmin, Ahmad Fauzan
Abd Manap, Nurulfajar
spellingShingle Hamzah, Rostam Affendi
Hamid, Mohd Saad
Kadmin, Ahmad Fauzan
Abd Manap, Nurulfajar
Stereo matching algorithm based on deep learning: a survey
author_facet Hamzah, Rostam Affendi
Hamid, Mohd Saad
Kadmin, Ahmad Fauzan
Abd Manap, Nurulfajar
author_sort Hamzah, Rostam Affendi
title Stereo matching algorithm based on deep learning: a survey
title_short Stereo matching algorithm based on deep learning: a survey
title_full Stereo matching algorithm based on deep learning: a survey
title_fullStr Stereo matching algorithm based on deep learning: a survey
title_full_unstemmed Stereo matching algorithm based on deep learning: a survey
title_sort stereo matching algorithm based on deep learning: a survey
publisher Elsevier B.V.
publishDate 2022
url http://eprints.utem.edu.my/id/eprint/26769/2/1-S2.0-S1319157820304493-MAIN.PDF
http://eprints.utem.edu.my/id/eprint/26769/
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