The Design And Implementation Of Moving Object Tracking System

Object detection and tracking has many applications in some area, including intelligent transport network, video content analysis and object behavior understanding. MMDTS is our system to detect and track multiple moving objects. In our systrem, a mixture gaussian is used to model the background. Then, blob features are grouped by using connected component label method and corner features are obtained by corner detection in the foreground. Finally, a multi-level feature tracking strategy is used to track independent object stably. Also, our extended system has three applications, object tracking recording, people and vehicle counting and vehicle reverse traveling warning.This paper's main research work is to design and implement the MMDTS system and three extended applications. MMDTS system is content of background model, feature extraction, feature tracking and prediction model. We select common and mature technology for the feature extraction and prediction model. Background model and feature tracking are the focus of the paper. Based on Mixed Gaussian Model we have two cosiderations, luminous correction and shadow removal in HSV color space to modeling the background. In the feature tracking part, we design a multi-level tarcking straegy to tracking independent object by matching blob feature, independent object feature and corner feature. Three levels of tracking information are used interact with each other, and it can adapt variety situations in practical. This means it has real application.MMDTS has been tested in multiple databases, and it has well performance in both detection and tracking objects. It can adapt luminous change and handle objects crossing. However, the system also has some shortcomings, such as objects overlaped at first time would be tracked as one independent object. Also, our extended system has three applications, object tracking recording, people and vehicle counting and vehicle reverse traveling warning.