Stereo matching algorithm based on deep learning: A survey

Journal of King Saud University: Computer and Information Sciences

NurulFajar Abd Manap¹  Ahmad Fauzan Kadmin²  Rostam Affendi Hamzah³  Mohd Saad Hamid⁴ 

[1] Elektronik, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia;Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia;;Fakulti Kejuruteraan Elektronik &;Fakulti Teknologi Kejuruteraan Elektrik &

关键词: Stereo matching algorithm;    Deep learning;    Convolutional neural network;    Artificial intelligence;   

DOI  :  

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown