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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

مقاله ISI انگلیسی اصلی
سال انتشار: 2020
فایل ISI انگلیسی اصلی ، با فرمت Pdf
تعداد صفحات فایل ISI انگلیسی اصلی: 32 صفحه