MRKDSBC: a distributed background modeling algorithm based on mapreduce

Authors:
Cong Wan;Cuirong Wang;Kun Zhang
Affiliations:
College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China
Venue:
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Year:
2012

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Abstract

Video surveillance is a widely used technology. Moving object detection is the most important content of video surveillance. Background modeling is an important method in moving object detection. However, background modeling algorithm is usually computationally intensive when the size of video is large. Kernel density estimation method based on Chebyshev inequality (KDSBC) is a new background modeling algorithm. This paper present MRKDSBC based on MapReduce which is a distributed programming model. Further more, we prove the correctness of the algorithm theoretically and implement it on Hadoop platform. Finally, we compare it with traditional algorithm.