Deep image acquisition technology based on deep learning

Qi Wang; Yan Piao

doi:10.1117/12.3008015

14 November 2023 Deep image acquisition technology based on deep learning

Qi Wang, Yan Piao

Proceedings Volume 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023); 129341B (2023) https://doi.org/10.1117/12.3008015
Event: 2023 3rd International Conference on Computer Graphics, Image and Virtualization (ICCGIV 2023), 2023, Nanjing, China

Abstract

Depth image estimation is an important technology in integral imaging display system and its image quality has been widely concerned by researchers. In recent years, more and more researchers extract the depth images of RGB images by deep learning. To obtain high-quality depth images and solve the problem of unclear edges and incomplete outlines, we add semantic segmentation module (SSM) to the depth estimation network (DEN) to share parameters of depth estimation and semantic segmentation (DE&SS). The SSM extracts multi-level semantic feature information, fuses global feature information and local feature information effectively, and guides depth estimation with more abundant semantic feature information to improve depth image quality. Experiments are carried out on the general datasets NYU-Depth V2 and KITTI. According to the experimental results, the depth images obtained by the proposed method have clearer edges and more complete outlines than that obtained by other advanced methods.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qi Wang and Yan Piao "Deep image acquisition technology based on deep learning", Proc. SPIE 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023), 129341B (14 November 2023); https://doi.org/10.1117/12.3008015

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