WSN are collection of spatially distributed autonomous actuator devices called sensor nodes. Target tracking under surveillance is one of the main applications of WSN. We introduce an edge detection algorithm to generate each face further in such a way that the nodes can prepare ahead of the target’s moving, which greatly helps tracking the target in a timely fashion and recovering from special cases, e.g., sensor fault, loss of tracking, Also, we develop an optimal selection algorithm to select which sensors of faces to query and to forward the tracking data. a new  tracking  framework,  called  Face Track,  which  employs  the  nodes  of  a  spatial region  surrounding a  target, called a  face. In target tracking, sensor nodes are informed when the target under surveillance is discovered. Some nodes detect the target and send a detection message to the nodes on the target’s expected moving path. So nodes can wake up earlier. Face tracking is a new tracking framework, in which divides the region into different polygons called faces. Instead of predicting the target location separately in a face, here estimate the targets movement towards another face. it enables the wireless sensor network to be aware of a target entering the polygon a bit earlier