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Fast tracking of semantic video object based on motion prediction and subregion extraction

机译:基于运动预测和子区域提取的语义视频对象快速跟踪

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Extraction quality and speed are two fundamental problems for semantic video object extraction. The paper introduces a novel fast-speed tracking algorithm for extracting semantic video objects from image sequences. First, the subregion that covers the contour of a semantic video object is extracted by using motion prediction and mathematical morphology operators to generate the inner and outer contour of the subregion. Then, an optimized tracking scheme is employed to track this particular subregion instead of the whole image. Results on real sequences show that this method greatly improves the processing speed compared to earlier tracking algorithms and that it keeps the quality of the extracted object. Therefore, it is a promising approach for real time processing systems based on video objects.
机译:提取质量和速度是语义视频对象提取的两个基本问题。本文介绍了一种新颖的快速跟踪算法,用于从图像序列中提取语义视频对象。首先,通过使用运动预测和数学形态学运算符提取覆盖语义视频对象轮廓的子区域,以生成子区域的内部和外部轮廓。然后,采用优化的跟踪方案来跟踪此特定子区域,而不是整个图像。实际序列的结果表明,与早期的跟踪算法相比,该方法极大地提高了处理速度,并保持了提取对象的质量。因此,对于基于视频对象的实时处理系统是一种很有前途的方法。

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