Research of a Particle Swarm Optimization Approach for Object Tracking

• Main Authors: Chuan-Yao Liu, 劉權耀
• Other Authors: 徐培倫
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/14883855167787741111

碩士 === 清雲科技大學 === 電子工程所 === 98 === Applications in the security system, automatically monitoring and tracking an object of the system, is a very important role. How to achieve real-time monitoring and tracking moving objects; such as, people, animals, vehicles, etc., is an important image processing research topic. In this thesis, the development of a monitoring and tracking system, mainly using background subtraction to detect moving image point, through a mixed-type Gaussian distribution model establishes a background of adaptation and use to determine the prospects for moving pixel detection pixels. Then, through the prospect of pixel color and shape to build a foreground object, and characteristics of the object using the value of future comparison, using the particle swarm optimization to find more precise center of mobile objects to achieve object tracking purposes. Through experimental designs and observations in different environments, our prototype system can track moving objects more accurately and effectively.