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An improved block matching algorithm for motion estimation in video sequences and application in robotics

机译:一种改进的视频序列运动估计的改进块匹配算法及机器人应用中的应用

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摘要

Block Matching is one of the most efficient techniques for motion estimation for video sequences. Metaheuristic algorithms have been used effectively for motion estimation. In this paper, we propose two hybrid algorithms: Artificial Bee Colony with Differential Evolution and Harmony Search with Differential Evolution based motion estimation algorithms. Extensive experiments are conducted using four standard video sequences. The video sequences utilized for experimentation have all essential features such as different formats, resolutions and number of frames which are generally required in input video sequences. We compare the performance of the proposed algorithms with other algorithms considering various parameters such as Structural Similarity, Peak Signal to Noise Ratio, Average Number of Search Points etc. The comparative results demonstrate that the proposed algorithms outperformed other algorithms.
机译:块匹配是视频序列运动估计最有效的技术之一。 已经有效地用于运动估计的成群质识别算法。 在本文中,我们提出了两个混合算法:具有差分演化和和谐搜索的人工蜜蜂群,基于差分演化的运动估计算法。 使用四个标准视频序列进行广泛的实验。 用于实验的视频序列具有诸如不同格式,分辨率和帧数之类的所有基本特征,这些功能通常在输入视频序列中所需的帧数。 我们将所提出的算法的性能与其他算法进行比较,考虑各种参数,例如结构相似性,峰值信号到噪声比,平均搜索点等的平均数。比较结果表明,所提出的算法优于其他算法。

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