Moving Object Detection Optimization Algorithm Based on Robust Principal Component Analysis

YANG Yizhong; WANG Pengfei; HU Xionglou; WU Nengju

doi:10.11999/JEIT170789

Volume 40 Issue 6

May 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(6): 1309-1315

YANG Yizhong, WANG Pengfei, HU Xionglou, WU Nengju. Moving Object Detection Optimization Algorithm Based on Robust Principal Component Analysis[J]. Journal of Electronics & Information Technology, 2018, 40(6): 1309-1315. doi: 10.11999/JEIT170789

Citation:

YANG Yizhong, WANG Pengfei, HU Xionglou, WU Nengju. Moving Object Detection Optimization Algorithm Based on Robust Principal Component Analysis[J]. Journal of Electronics & Information Technology, 2018, 40(6): 1309-1315. doi: 10.11999/JEIT170789

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Moving Object Detection Optimization Algorithm Based on Robust Principal Component Analysis

doi: 10.11999/JEIT170789

Funds:

The National Natural Science Foundation of China (61401137, 61404043), The Key Science and Technology Project of Anhui Province (16030901007), The Fundamental Research Funds for the Central Universities (J2014HGXJ0083)

Received Date: 2017-08-04
Rev Recd Date: 2018-01-10
Publish Date: 2018-06-19

Abstract

Abstract

Since dynamic background may be erroneously detected as a moving object in the Robust Principal Component Analysis (RPCA) algorithm, a RPCA-based moving object detection optimization algorithm is proposed to improve it. After detected by the RPCA algorithm, the moving object will be separated from dynamic background according to the Gaussian distribution of dynamic background in the time domain and the difference of mean value and variance between dynamic background and moving object in the whole video stream. The results show that the algorithm can deal with dynamic background effectively and detect the moving objects well.
- Moving object detection,
- Robust Principal Component Analysis (RPCA),
- Dynamic background,
- Time domain

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References(21)

References

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