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Page 133 Tang et al. Intell Robot 2022;2(2):130­44 I http://dx.doi.org/10.20517/ir.2022.07

Two consecutive
frames Count the number of
changing pixels

The previous Background updating
Input video few frames Establish the initial
sequence background model

Edge Foreground Shadow
detection detection removal
based on based on based on
Canny ViBE HSV color
method method space

Output the
detection results

Figure 1. Flow diagram of the improved ViBe-based approach for moving object detection.

tation threshold, which can also obtain a better performance in complex dynamic backgrounds but cannot
effectively remove shadows.

3. METHODS
In this paper, the problem of moving object detection based on ViBe method is studied. The basic idea of the
ViBe method uses neighboring pixels to establish the background model and then compares the background
model with the current pixel value to detect the foreground. There are three main steps in the ViBe method,
namely the background initialization, the foreground object detection, and the background model updating.
Aiming at the problems in the three main steps, some improvements are proposed in this study. The flow chart
of the proposed approach is shown in Figure 1 and the main steps of the proposed approach are introduced in
detail as follows.

3.1. Mode method based background modeling
The initial background selection is the first step in the ViBe-based method, which will directly influence the
detection results. If it can be extracted correctly, the accuracy of the object detection will increase. In general,
the ViBe method uses the first frame as the initial background [41] , namely

( , ) = ( , ) (1)

where ( , ) is the pixel value of the background and ( , ) is the pixel value of the first frame in the video.
Although the method using the first frame is simple and efficient, it will fail when there is a moving object
in the first frame. To deal with this problem, some improvements are proposed, such as the mean method,
which needs to store more video frames and has the problem of shadows [42] . In this paper, the mode method
is introduced to extract the initial background frame [43] . The basic idea of the mode method for background
modeling is that few previous frames are used to obtain an optimized background model. The pixel value of