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 three stages they are background elimination, foreground detection using Gaussian Mixture Model and object tracking using 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. Multiple People Tracking using Contextual
1.A Gaussian Mixture Model (GMM) is a parametric probability density function represented as a weighted sum of Gaussian component densities. GMMs are commonly used as a parametric model of the probability distribution of continuous measurements or features in a biometric system, such as color based tracking of an object in video.
2.In many computer related vision technology, it is critical to identify moving objects from a sequence of videos frames. In order to achieve this, background subtraction is applied which mainly identifies moving objects from each portion of video frames.
3.Background subtraction or segmentation is a widely used technique in video surveillance, target recognitions and banks. By using the Gaussian Mixture Model background model, frame pixels are deleted from the required video to achieve the desired results.
The application of background subtraction involves various factors which involve developing an algorithm which is able to detect the required object robustly, it should also be able to react to various changes like illumination, starting and stopping of moving objects.
Surveillance is the monitoring of the behavior, activities or other changing information usually of people and often in a surreptitious manner. Video surveillance is commonly used for event detection and human identification. But it is not easy as think to detect the event or tracking the object.
There are many techniques and papers introduced by many scientists for the backend process in the video surveillance. Different automated software’s are used for the analysis of the video footage. It tracks large body movements and objects
Gaussian Mixture Model