|Moving Object Detection for a Moving Camera Based on Global Motion Compensation and Adaptive Background Model
Yang Yu, Laksono Kurnianggoro, and Kang-Hyun Jo*
International Journal of Control, Automation, and Systems, vol. 17, no. 7, pp.1866-1874, 2019
Abstract : A fast and effective moving object detection method for a moving camera is proposed in this paper.
The global motion is estimated through tracking the grid-based key points using optical flow. After the motion
compensation, the background model, candidate background model and candidate age are used for the background modelling. Then the local pixel difference and the consistency of local changes between the current frame and the
background model are used for the background subtraction. The lighting influence threshold and the local pixel
difference between the current frame and two previous aligned frames are used to reduce the lighting influences.
Finally, Gaussian filter, connected-components analysis, erosion and dilation are used to refine the results. The
performance evaluation shows that this proposed method works very fast in real time and has competitive results
compared with others in the public dataset.
Background subtractionhomography matrix, motion compensation, object detection, optical flow.
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