Region-Based Motion Analysis and 3D Reconstruction for a Translational Video Sequence

Xiaodong Huang, E. Dubois
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引用次数: 0

Abstract

This paper presents a hybrid 1D motion estimation algorithm which combines pixel-based and region-based approaches that can give depth images from translational video sequences with very high quality. Firstly, we combine the motion information estimated by a variational regularization approach and by the Gabor transform through histogram analysis to identify those regions with zero motion (like for the sky). Then another round of region matching is carried out to refine the motion values for the other regions. Our algorithm can detect most of the sky regions segmented by foreground objects with complex geometry while keeping the boundaries of moving objects sharp and clear, which is an very important feature to obtain accurate 3D models. The high quality motion maps/depth images obtained by our algorithm are shown along with 3D reconstructions from novel viewpoints.
基于区域的平移视频序列运动分析与三维重建
本文提出了一种混合一维运动估计算法,该算法结合了基于像素和基于区域的方法,可以从平移视频序列中获得非常高质量的深度图像。首先,通过直方图分析,将变分正则化方法估计的运动信息与Gabor变换估计的运动信息结合起来,识别出无运动的区域(如天空)。然后进行另一轮区域匹配,以细化其他区域的运动值。我们的算法可以检测出大部分由复杂几何形状的前景物体分割的天空区域,同时保持运动物体边界的清晰,这是获得精确的三维模型的一个非常重要的特征。我们的算法获得了高质量的运动地图/深度图像,并从新的视点进行了三维重建。
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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