Knowledge-Based Coding of Objects for Multisource Surveillance Video Data

Knowledge-Based Coding of Objects for Multisource Surveillance Video Data
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多源监控视频数据的基于知识的对象编码

DOI:
10.1109/tmm.2016.2581590
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发表时间:
2016-09
影响因子:
7.3
通讯作者:
Xiong Zixiang
Xiong Zixiang
中科院分区:
计算机科学1区
文献类型:
--
作者:
Xiao Jing;Hu Ruimin;Liao Liang;Chen Yu;Wang Zhongyuan;Xiong Zixiang

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全局对象冗余(GOR)是多源监控视频数据(MSVD)中常见的一种新的冗余形式,与单个视频片段中的局部空间/时间冗余相反。GOR是由前景物体在多个相机上的重复引起的,并且随着物体数量的增加而变得有影响。消除GOR大大提高了MSVD编码效率。为了实现这一目标,本研究首先在仔细分析GOR组成的基础上提出了一种基于知识的对象表示。该表示包含恒定部分和变分部分:前者用于表示对象在多个相机上共享的公共知识,而后者用于表示对象表面的局部变化。在此基础上,提出了一种基于知识的编码(KBC)方法,其中每个前景目标都使用混合预测方案进行编码,其中目标的恒定部分通过模型库的全局预测生成,而变化部分通过基于姿态的局部参考帧进行短期预测。实验结果表明,KBC方法对高分辨率视频片段中前景对象的编码平均节省39%以上的比特(而对整个视频的编码平均节省16%)。将所提出的编码方法应用于大空间和时间尺度的监控视频,可以节省PB级的存储空间。
Global object redundancy (GOR), as opposed to local spatial/temporal redundancies in a single video clip, is a new form of redundancy common in multisource surveillance video data (MSVD). GOR is induced by the repetition of foreground objects across multiple cameras, and becomes influential as the number of objects increases. Eliminating GOR considerably improves MSVD coding efficiency. In an effort to accomplish this, this study first proposes a knowledge-based representation of objects based on careful analysis of GOR composition. The representation contains a constant part and a variational part: the former is used to represent the common knowledge shared by an object across multiple cameras, while the latter is used to represent local variations on the object's surfaces. Based on the proposed representation, a knowledge-based coding (KBC) method is then proposed in which each foreground object is encoded with a hybrid prediction scheme, where the constant part of the object is generated via global prediction from a model library and the variational part is predicted via local reference frames with pose-based, short-term prediction. Experimental results showed that the KBC method saves more than 39% bits on average for encoding foreground objects in high-resolution video clips (compared to 16% for the entire videos). Applying the proposed coding method to surveillance videos in large spatial and temporal scale allows storage savings at the PB level.
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