Tracking Multiple Moving Objects Using Gaussian Mixture Model

The advance of technology makes video acquisition devices better and less costly, thereby increasing the number of applications that can effectively utilize digital video. Compared to still images, video sequences provide more information about how objects and scenarios change over time. For object recognition, navigation systems and surveillance systems, object tracking is an indispensable first-step. The conventional approach to object tracking is based on the difference between the current image and the background image. The algorithms based on the difference image are useful in extracting the moving objects from the image and track them in consecutive frames. The proposed algorithm, consisting of three stages i.e. color extraction, foreground detection using Gaussian Mixture Model and object tracking using Blob Analysis. Initially color extraction is done to extract the required color from a particular picture frame, after color extraction the moving objects present in the foreground are detected using Gaussian Mixture Model and Blob Analysis is applied on consecutive frames of video sequence, so as to observe the motion of the object, hence the moving object in the video sequences will be tracked.