Depth Extraction from Monocular Video Using Bidirectional Energy Minimization and Initial Depth Segmentation

Chunyu Lin, J. D. Cock, Jürgen Slowack, P. Lambert, R. Walle
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引用次数: 1

Abstract

In this paper, we propose to extract depth information from a monocular video sequence. When estimating the depth of the current frame, the bidirectional energy minimization in our scheme considers both the previous frame and next frame, which promises a much more robust depth map and reduces the problems associated with occlusion to a certain extent. After getting an initial depth map from bidirectional energy minimization, we further refine the depth map using segmentation by assuming similar depth values in one segmented region. Different from other segmentation algorithms, we use initial depth information together with the original color image to get more reliable segmented regions. Finally, detecting the sky region using a dark channel prior is employed to correct some possibly wrong depth values for outdoor video. The experimental results are much more accurate compared with the state-of-the-art algorithms.
基于双向能量最小化和初始深度分割的单目视频深度提取
本文提出了从单目视频序列中提取深度信息的方法。在估计当前帧的深度时,我们的方案中的双向能量最小化同时考虑了前一帧和下一帧,这保证了一个更加鲁棒的深度图,并在一定程度上减少了与遮挡相关的问题。在从双向能量最小化中得到初始深度图之后,我们通过在一个分割区域中假设相似的深度值来进一步细化深度图。与其他分割算法不同的是,我们将初始深度信息与原始彩色图像结合使用,得到更可靠的分割区域。最后,利用暗通道先验检测天空区域,修正一些可能错误的户外视频深度值。与现有算法相比,实验结果更加准确。
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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