In this paper we propose an efficient real-time communication mechanism for distributed vision processing. One of the biggest problems of distributed vision processing, as is the same as in other distributed systems, is how to reduce the overhead of communication among computation nodes. In vision processing, we have to deal with a lot of time varying variables, some of which are large in size, and, therefore, the efficiency of sending and receiving of those variables is essential. To solve the problem, we propose Accuracy-driven Memory architecture, whose key idea is based on imprecise computation model and predictive coding. Here, we will present the basic framework of Accuracy-driven Memory architecture and show its efficiency based on some simulation results.