| Summary: | 碩士 === 國立臺灣大學 === 電機工程學研究所 === 97 === As a result of the need of military and social security, image analysis and object tracking has become the field studied popularly in the recent years. Image analysis and object tracking consist of two main steps ‘foreground extraction’ and ‘object analysis and tracking’. The result of foreground extraction has the significant influence on the accuracy of object analysis and tracking, so this paper emphasizes the efficiency and accuracy of background generation and foreground extraction. Firstly, this paper implements many simple and popular background generation and foreground extraction algorithms, then analysis the advantage and disadvantage. Secondly, this paper also presents a new method of background generations that fulfill the requirement of real-time and reduce the usage of memory. For foreground extraction, this system detects and removes shadow by sobel filter.
Object tracking is performed by applying a kalman filter to predict and correct the trajectory and size change of object. In addition, tracking and recognition of merge and split of multiple objects are also available. This system may depend on the user’s goal and let user define freely the feature of object which would be tracked, the region would be monitored and the activity would let the system make an alert.
This system passed through many testing videos, including in-door, out-door, mix of human and vehicle, the highway and the high-noise environment. In addition, to test and evaluate the algorithm and method, this work deploys the system in a real living environment out of our lab. The experiment result present that this system have good efficiency in real-time and high accuracy, it is also flexible and robust.
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