Network oriented motion estimation for video-on-demand over wireless networks

Motion estimation is being shown to be very helpful in the compression of video sequences. However, most of the motion estimation algorithms require a large amount of computation making them undesirable to be used for the power constrained applications such as battery operated wireless terminals having video encoders. The present network oriented motion estimation algorithm reduces the power dissipation of wireless video devices in a network environment by exploiting the predictability of object motion. Since the location of an object can be predicted from its location in previous frames, so it is possible to optimally partition the motion estimation computation between the portable devices and high-powered compute servers on the wired network. Thus, in network oriented motion estimation (NOME) a remote high-powered resource at the base station (or on the wired network) predicts the motion vectors of the previous frames. The base station sends these motion predicted motion vectors to a portable video encoder where motion compensation proceeds as usual. The algorithm achieves a reduction in the number of operations performed at the encoder for motion estimation by 3-10 orders of magnitude while introducing some minimal degradation to the decoded video based on the quantization threshold chosen