EPJ Web Conf.
Volume 224, 2019IV International Conference “Modeling of Nonlinear Processes and Systems” (MNPS-2019)
|Number of page(s)||4|
|Section||Machine Learning, Artificial Intelligence and High-Performance Computing|
|Published online||09 December 2019|
Modified Depth-Map Inpainting Method Using the Neural Network
Don Sate Technical University, RU-344000, Rostov-on-Don, Russia
2 Moscow State Technological University “STANKIN”, RU-127055, Moscow, Russia
3 School of Computer & Information Technology, Beijing Jiaotong University, Beijing, China
* e-mail: firstname.lastname@example.org
Published online: 9 December 2019
This paper proposes a method for reconstructing a depth map obtained using a stereo pair image. The proposed approach is based on a geometric model for the synthesis of patches. The entire image is preliminarily divided into blocks of different size, where large blocks are used to restore homogeneous areas, and small blocks are used to restore details of the image structure. Lost pixels are recovered by copying the pixel values from the source based on the similarity criterion. We used a trained neural network to select the “best like” patch. Experimental results show that the proposed method gives better results than other modern methods, both in subjective and objective measurements for reconstructing a depth map.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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