Modeling Of Moving Object Detection Using GCM Alert System
Abstract- In previous model image stored in the server it takes time to retrieve after detecting by estimating the absolute
difference between incoming video frame and background model. In addition to this thesis, we present an operational
computer vision for real-time observing, detection and tracking of human motion in a tough area. To efficiently observe such
a wide area at less-cost, mobile robots are an attractive options. The moving object is identified using the Cauchy
distribution model. Using threshold value the detected pixel is identified. The movement of the object is identified exactly.
After motion detection it will send a GCM alert to the android mobile application. Experimental results show that the
algorithm is very effective and provides rapid comparison between pixel of current frame and ability to minimize both false
and missed detection.