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Feature Point Video Synthesis for tagged vehicular traffic

机译：用于标记车辆交通的特征点视频合成

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A novel video compression algorithm is proposed in this paper called Feature Point Video Synthesis (FPVS) for vehicular traffic along a lane. Using this algorithm, the video data can be stored by keeping just a few parameters and then playing back the synthesized replica of the original video. This new idea is significant because unlike CCTV cameras, the proposed algorithm allows for only few parameters to keep a record of video data, thus saving a lot of disk space and bandwidth. Using different simulation scenarios, FPVS has been found to save more than 99% video bit-rate as compared to normal video compression techniques specifically for vehicular traffic. Besides the said advantages, the idea is important to add intelligence in vehicular traffic data; hence the video traffic can be utilized in intelligent transportation system. Only those parts of the algorithm are explained in this paper that deal with tagged vehicles. The proposed system is important because a high quality video display at the receiving end is possible from the fetched variables.
机译：本文提出了一种新颖的视频压缩算法，称为特征点视频合成（FPVS），用于沿车道的车辆通行。使用此算法，可以通过仅保留几个参数然后播放原始视频的合成副本来存储视频数据。这一新想法意义重大，因为与CCTV摄像机不同，该算法仅允许很少的参数来记录视频数据，从而节省了大量磁盘空间和带宽。与专用于车辆交通的普通视频压缩技术相比，使用不同的仿真方案，已发现FPVS可以节省超过99％的视频比特率。除了上述优点外，该想法对于在车辆交通数据中增加情报也很重要。因此，视频流量可用于智能交通系统。在本文中，仅解释了算法中涉及标记车辆的那些部分。所提出的系统很重要，因为根据所获取的变量可以在接收端进行高质量的视频显示。

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