Dense depth recovery based on adaptive image segmentation

Shangli Liang, C. Yuan
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引用次数: 2

Abstract

Stereoscopic vision has been a hot research topic in recent years. As one of the most important steps for 3D reconstruction from image sequences, dense depth recovery has attracted much attention in computer vision recently. A lot of efficient algorithms based on stereo matching have been proposed. But the difficulties in depth recovery are not overcome completely yet. In this paper, we aim at the main problems of depth recovery and propose our solutions. And an effective approach for dense depth recovery based on adaptive image segmentation is also presented. Experiments show that accurate depth results can be achieved through the proposed approach.
基于自适应图像分割的密集深度恢复
立体视觉是近年来的研究热点。密集深度恢复作为图像序列三维重建的重要步骤之一,近年来在计算机视觉领域受到了广泛的关注。人们提出了许多基于立体匹配的高效算法。但深度开采的困难还没有完全克服。本文针对深度开采中存在的主要问题,提出了相应的解决方案。提出了一种有效的基于自适应图像分割的密集深度恢复方法。实验结果表明,该方法可以获得准确的深度结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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