A New Symmetric-Object Oriented Approach for Motion Estimation in Wireless Multimedia Sensor Networks

Motion estimation is a process of determining motion vectors. It is an essential challenge in digital video processing and computer vision. Therefore, It does not fit critical condition applications and constricted resource systems such as Wireless Multimedia Sensor Networks (WMSN). The main objective of the motion estimation is powerfully reducing temporal redundancy between successive frames to achieve significant video compression. In this paper, we propose a novel symmetric-object oriented approach for motion estimation in WMSN, called SYMO-ME. Our goal is to reduce the high complexity of motion estimation process. We also introduce a new motion estimation energy consumption model for block matching algorithms (BMAs) in WMSNs. This model depends on the energy consumption value of different executed instructions. Simulation results confirm the efficiency of our proposition in reducing the total number of search points for finding the motion vectors over a video frame compared with a group of considered BMAs, and improving the WMSN life time by saving the limited resources.