# Study on Bridge Displacement Monitoring Algorithms Based on Multi-Targets Tracking
## 1 Introduction  
Due to the frequent occurrence of structural constructions' safety accidents in recent years, the national property and people's lives have suffered tremendous losses. Hence, it is deeply recognized that real-time online monitoring and health assessment of structural constructions, especially those newly built, are very important. In view of the emergence of new structural constructions, long-span bridges, and complex system buildings, the health monitoring and safety assessment of structures should be paid more attention. Structural displacement, as a key index of structural safety evaluation, can directly reflect whether the deformation of bridge structure exceeds its safety permission. It can provide effective parameters for structural damage identification and health monitoring. Displacement monitoring can be applied to wood [1], bridges [2], dams [3], anti-lock brake systems [4], stay cables [5], and vibration analysis in vitro imaging systems [6], etc. For structural construction like bridges, there are still a lot of contact displacement monitoring methods in use, such as acceleration sensor and displacement meter [7], Global Positioning System (GPS) [8], electronic total station [9], laser interferometer [10], and so on. Contact monitoring methods often need to install sensors on bridges, which makes the maintenance of sensors become very difficult in the later period because of bridges' often crossing the sea or rivers. In order to overcome these limitations, non-contact displacement monitoring methods have gradually emerged in recent years. Among them, the Digital Image Processing (DIP) method stands out for its high accuracy and simple installation of equipment. At present, the Digital Image Correlation (DIC) [11; 12; 1; 1; 5; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22] method is the mainstream for bridge displacement monitoring using DIP. DIC, also called digital speckle correlation, is to obtain the deformation information of the Region of Interest (ROI) from two digital images before and after deformation. The image beforedeformation can be called the reference image and the image after deformation can be called the deformed image. The basic principle of DIC is to mesh the ROI in the reference image, treat the motion of each sub-region as a rigid motion, and calculate the correlation according to the pre-defined correlation function through a certain search method for each sub-region. In the deformed image, the location of the sub-region after deformation is the region whose cross-correlation coefficient with the sub-region in the reference image is the maximum, and then the displacement of the sub-region is obtained. By calculating all the sub-regions, the deformation information of the whole field can be obtained. The DIC method is welcomed by some scholars because it is easy to implement and its calculation accuracy is high. Despite its great advantages, the DIC method has to carry out more tedious data processing in order to obtain better measurement results. Its computational efficiency can not meet the requirements of fast measurement. In the process of a speckle image's acquisition and transmission, there are also many factors (such as signal noise, data missing, etc.) that affect the accuracy of measurement results. Therefore, how to better apply the DIC method to the actual measurement; there are still many research works to be further improved [4; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22]. Target tracking [23; 24; 25; 26], as its name implies, is to locate the position of a specific target in each frame of the image and generate the motion trajectory of the target. Setting a target board on the point which needs displacement monitoring, the displacement of the point can be known by the target board's displacement after processing the sampled image. The target board for sampling is designed with special geometric patterns, which Light Emitting Diode (LED) lights.