Abstract
Moving target detection (MTD) is one of the emphases and difficulties in the field of computer vision and image processing. It is the basis of moving target tracking and behavior recognition. We propose two methods are improved and fused, respectively, and the fusion algorithm is applied to the complex scene for MTD, so as to improve the accuracy of MTD in complex and hybrid scenes. Using the main idea of the three‐frame difference image method, the background difference method and the interframe difference method are combined to make their advantages complementary to overcome each other’s weaknesses. The experimental results show that the method can be well adapted to the situation of periodic motion interference in the background, and it can adapt to the situation of sudden background changes.
Highlights
In recent years, the methods of video moving target detection (MTD) have been deeply studied and some problems existing in algorithms have been improved, most of these algorithms are for specific applications [1]
In the case where the pixel values of the two frames before and after the volume change are small, we can separate the moving target and the background according to the frame difference method. e frame difference method is the simplest MTD method among all the current MTD methods
Principle block diagram of TFDM is shown in Figure 3. e specific process of MTD by TFDM is as follows
Summary
The methods of video moving target detection (MTD) have been deeply studied and some problems existing in algorithms have been improved, most of these algorithms are for specific applications [1] It is the follow-up tracking and recognition of moving objects and the basis of semantic understanding of moving object sequences [2,3,4]. E Defense Advanced Research Agency’s Airborne Video Surveillance (AVS) program uses target detection technology to capture static or dynamic moving target information from video in real time and combines moving target tracking and recognition technology to obtain moving target speed, position, and trajectory information. Using such moving target information can improve the real-time detection function of UAV for specific environment [14]
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