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- Kurzbeschreibung<p>Master's Thesis from the year 2014 in the subject Computer Science - Miscellaneous, grade: 9.2, , language: English, abstract: In this thesis we present an operational computer video system for moving<br>object detection and tracking . The system captures monocular frames of<br>background as well as moving object and to detect tracking and identifies<br>those moving objects. An approach to statistically modeling of moving object<br>developed using Background Subtraction Algorithms. There are many<br>methods proposed for Background Subtraction algorithm in past years.<br>Background subtraction algorithm is widely used for real time moving object<br>detection in video surveillance system. In this paper we have studied and<br>implemented different types of methods used for segmentation in Background<br>subtraction algorithm with static camera. This paper gives good understanding<br>about procedure to obtain foreground using existing common methods of<br>Background Subtraction, their complexity, utility and also provide basics which<br>will useful to improve performance in the future . First, we have explained the<br>basic steps and procedure used in vision based moving object detection.<br>Then, we have debriefed the common methods of background subtraction like<br>Simple method, statistical methods like Mean and Median filter, Frame<br>Differencing and W4 System method , Running Gaussian Average and<br>Gaussian Mixture Model and last is Eigenbackground Model. After that we<br>have implemented all the above techniques on MATLAB software and show<br>some experimental results for the same and compare them in terms of speed<br>and complexity criteria. Also we have improved one of the GMM algorithm by<br>combining it with optical flow method, which is also good method to detect<br>moving elements.</p>
- AutorPriyank Shah
- Seiten64 Seiten
- Gewicht105 g
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