非凸运动辅助低秩稀疏分解目标检测算法

doi:10.3969/j.issn.1001-506X.2020.06.03

Abstract

Abstract:

Aiming at the problem of low detection accuracy when using the traditional low rank and sparse decomposition (LRSD) algorithm for video moving object detection, this paper proposes a moving object detection algorithm based on the robust nonconvex motion-assisted LRSD (RNMALRSD). Firstly, the proposed algorithm considers the low rank characteristic of the background, and utilities the nonconvex γ norm to approximate the rank function. It also considers that the background is still sparse in the transform domain, and introduces the sparse prior of the background in its transform domain. In addition, the motion-assisted information matrix is introduced into the foreground motion information to show the possibility that each pixel belongs to the background and improve the accuracy of video moving object detection. Then, the proposed model is solved by the alternating direction method of multipliers (ADMM). Finally, the proposed method is applied to moving object detection. The experimental results show that the proposed RNMALRSD method has a higher detection accuracy than other moving object detection methods based on LRSD.

Key words: low rank and sparse decomposition (LRSD), motion-assisted, alternating direction method of multipliers (ADMM), robust principal component analysis (RPCA), object detection

CLC Number:

TN912.3

Zhenzhen YANG, Jun LE, Yongpeng YANG, Lu FAN. Object detection algorithm of nonconvex motion-assisted low rank and sparse decomposition[J]. Systems Engineering and Electronics, 2020, 42(6): 1218-1225.

Figures/Tables 3

Fig.1

Table 1

Table 2

References 30

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算法	视频帧
算法	Bootstrap	ShoppingMall	Office	WaterSurface	Highway	Backdoor	BusStation	平均值
RNMALRSD	0.742 7	0.739 5	0.836 6	0.812 4	0.733 3	0.612 9	0.776 3	0.750 0
MAMR	0.742 3	0.734 5	0.823 5	0.798 3	0.729 6	0.609 7	0.772 7	0.744 4
LRSD-TNNSR	0.666 0	0.732 7	0.711 8	0.787 5	0.731 5	0.607 7	0.763 2	0.714 3
GoDec	0.738 7	0.683 0	0.691 1	0.761 4	0.725 5	0.574 7	0.721 0	0.699 3
PCP	0.705 2	0.718 5	0.496 6	0.776 1	0.708 1	0.611 3	0.760 9	0.682 4
LRSD-ATNN	0.658 8	0.719 2	0.733 5	0.806 7	0.713 0	0.602 1	0.754 1	0.712 5
NRPCA	0.679 2	0.718 5	0.739 3	0.785 3	0.731 2	0.609 4	0.772 6	0.719 4

算法	视频帧
算法	Bootstrap	ShoppingMall	Office	WaterSurface	Highway	Backdoor	BusStation	平均值
RNMALRSD	0.738 5	0.729 3	0.759 8	0.807 5	0.732 3	0.611 2	0.741 5	0.731 5
MAMR	0.737 5	0.726 1	0.713 4	0.774 5	0.703 6	0.607 0	0.738 4	0.714 4
LRSD-TNNSR	0.651 8	0.720 8	0.520 5	0.768 4	0.703 3	0.608 6	0.719 6	0.670 4
GoDec	0.719 7	0.707 4	0.600 3	0.753 6	0.701 5	0.574 0	0.694 9	0.678 8
PCP	0.691 2	0.710 5	0.493 5	0.772 7	0.661 0	0.593 0	0.647 3	0.652 7
LRSD-ATNN	0.651 4	0.719 7	0.510 4	0.794 0	0.702 6	0.599 5	0.718 7	0.670 9
NRPCA	0.682 4	0.726 9	0.640 5	0.765 6	0.700 5	0.606 1	0.687 3	0.687 0

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Object detection algorithm of nonconvex motion-assisted low rank and sparse decomposition

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