摘要: 计算能力瓶颈限制了复杂视频事件检测算法在实时系统上的应用。为此,设计一种基于Map Reduce模型的分布式视频处理平台,用算子和算子间连接关系描述算法,将算法在时域上切分为并行计算的独立任务。采用普通计算机搭建基于该模型的视频处理集群,运行按模型组织的视频处理算法。实验结果表明,对于处理密集型的视频分析算法,系统处理能力随集群计算机数量的增加呈近似线性增长,能够满足实时处理需求,具有较强的可扩展性。
关键词:
机器视觉,
分布式计算,
视频分析,
视频并行处理,
集群计算,
实时视频处理
Abstract: Most advanced video incident detection algorithms are hard to apply in real-time systems because of its complexity. A distribute video processing platform based on Map Reduce is presented to solve the computation bottleneck, through which video processing algorithm is paralleled on time domain. A distributed video processing architecture is implemented with general-purpose computer. Test experiment proves the flexibility of system’s computation ability.
Key words:
machine vision,
distributed computation,
video analysis,
video parallel processing,
cluster computation,
real-time video processing
中图分类号:
耿晨曜, 姚丹亚, 张盈盈, 张煦, 常刚. 基于Map Reduce的分布式视频处理平台[J]. 计算机工程, 2012, 38(10): 280-283.
GENG Chen-Yao, TAO Dan-E, ZHANG Ying-Ying, ZHANG Xiu, CHANG Gang. Distributed Video Processing Platform Based on Map Reduce[J]. Computer Engineering, 2012, 38(10): 280-283.