Video surveillance using raspberry Pi with particle filtering

—One of the fundamental problem in vision is that of tracking objects through sequences of images. Within this report the design of Particle filter algorithm to track the target and show the resulting improvement in tracking. More specifically, this project described the technique of how to track Moving Object. The proposed architecture is suitable for indoors and outdoors scenes with static background and overcomes the problem of stationary targets fading into the background. Optimal estimation problems for nonlinear non-Gaussian state-space models do not typically admit analytic solutions. Since their introduction in 1993, particle filtering methods have become a very popular class of algorithms to solve these estimation problems numerically in an online manner, i.e. recursively as observations become available, and are now routinely used in fields as diverse as computer. The real time video surveillance using a system equipped for sensor support data is being developed to provide situational in the target of interest & also provide a safe means of video surveillance in the target place using raspberry pi