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Block Operator Context Scanning for Commercial Tracking

机译:块运营商上下文扫描以进行商业跟踪

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The industry that designs and promotes advertising products in television channels is constantly growing. For effective market analysis and contract validation, various commercial tracker systems are employed. However, these systems mostly rely on heuristics and, since commercial broadcasting varies significantly, are often inaccurate. This paper proposes a commercial tracker system based on the Block Operator Context Scanning (Block - OCS) algorithm, which is both accurate and fast. The proposed method, similar to coarse-to-fine strategies, skips a large portion of the image sequences by focusing only on Regions of Interest. In this paper, a video matching algorithm is also proposed, which compares image sequences using time sliding windows of frames. Experimental results showed 100% accuracy and 50% speed increase compared to traditional block-based processing methods.
机译:在电视频道中设计和推广广告产品的行业正在不断发展。为了进行有效的市场分析和合同确认,采用了各种商业跟踪系统。但是,这些系统主要依赖于启发式技术,并且由于商业广播差异很大,因此通常不准确。本文提出了一种基于块算子上下文扫描(Block-OCS)算法的商业跟踪系统,该系统精确且快速。所提出的方法类似于从粗到细的策略,通过仅关注目标区域来跳过图像序列的很大一部分。本文还提出了一种视频匹配算法,该算法使用帧的时间滑动窗口比较图像序列。实验结果表明,与传统的基于块的处理方法相比,精度提高了100%,速度提高了50%。

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