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arXiv · 1902.06255

Exploring Stereovision-Based 3-D Scene Reconstruction for Augmented Reality

Guang-Yu Nie·Yun Liu·Cong Wang·Yue Liu·Yongtian Wang
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Abstract

Three-dimensional (3-D) scene reconstruction is one of the key techniques in Augmented Reality (AR), which is related to the integration of image processing and display systems of complex information. Stereo matching is a computer vision based approach for 3-D scene reconstruction. In this paper, we explore an improved stereo matching network, SLED-Net, in which a Single Long Encoder-Decoder is proposed to replace the stacked hourglass network in PSM-Net for better contextual information learning. We compare SLED-Net to state-of-the-art methods recently published, and demonstrate its superior performance on Scene Flow and KITTI2015 test sets.

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Guang-Yu Nie, Yun Liu, Cong Wang, Yue Liu, Yongtian Wang. 2019-02-17. Exploring Stereovision-Based 3-D Scene Reconstruction for Augmented Reality. https://arxiv.org/abs/1902.06255

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