Network driven motion estimation for portable video terminals

Motion estimation has been shown to help signi cantly in the compression of video sequences. However, since most motion estimation algorithms require a large amount of computation, it is undesirable to use them in power constrained applications, such as battery operated wireless video terminals. This paper presents an approach to reducing the power dissipation of wireless video terminals in a networked environment by exploiting the predictability of object motion. Since the location of an object in the current frame can be predicted from its location in previous frames, it is possible to optimally partition the motion estimation computation between battery operated portable devices and high powered compute servers on the wired network. This can achieve a reduction in the number of operations performed at the encoder for motion estimation by over two orders of magnitude while introducing minimal degradation to the decoded video compared with full search encoder-based motion estimation.