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Disparity estimation based 3-D video object segmentation

机译:基于视差估计的3D视频对象分割

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摘要

Stereo video object segmentation is a critical technology of the new generation of video coding, video retrieval and other emerging interactive multimedia field. Determinations of distinctive depth of a frame features have become more and more popular in everyday life for automation industries like machine vision and computer vision technologies. This paper deals with the evaluation of the depth cues through dense of two frame stereo correspondence method. Experimental results show that the method can segment the stationary and moving objects both with better accuracy and robustness. The contributions are gaining higher accuracy in matching and reducing time of convergence.
机译:立体视频对象分割是新一代视频编码,视频检索和其他新兴的交互式多媒体领域的一项关键技术。在机器视觉和计算机视觉技术等自动化行业的日常生活中,确定框架特征的独特深度已变得越来越普遍。本文通过对两帧立体对应方法的密集度来评估深度线索。实验结果表明,该方法可以对静止和运动物体进行分割,具有较高的精度和鲁棒性。这些贡献在匹配和减少收敛时间方面获得了更高的准确性。

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