Moving Objects Detection Based on the Precise Background Compensation Under Dynamic Scene

Moving Objects Detection Based on the Precise Background Compensation Under Dynamic Scene

Yan Wang, Yang Yu, Gang Yan, Yingchun Guo
DOI: 10.4018/ijapuc.2014010104
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Abstract

In order to detect the moving object under dynamic scenes accurately, this paper proposes a moving object detection method which is based on the precise background compensation. First, the SURF (Speeded-Up Robust Features) algorithm is used to extract feature points, and the BBF(Best-Bin-First) search algorithm is adopted to match feature points, in addition the reverse constraint strategy is employed to remove the mismatching points. To enhance the accuracy of the background compensation, a dynamic threshold is set to remove the target feature points influence for the global motion parameters. At last, a combination of interval three-frame- -differencing and morphological method is used to detect the moving objects. Experimental results show that this method has good performance on multiple moving targets detection.
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The Overall Process Of The Algorithm

This algorithm includes three steps as followings:

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