The correlation characteristics of Multiview video (MVV) are influenced by the content of thevideo, illumination change, speed of moving objects andcameras, camera distance, frame rate, etc. In this paper, a framework of Multi-modal multi-view video coding(MMVC) is proposed on the basis of correlation analysisto achieve optimal performances among high compressioneffciency, low complexity, low memory cost, view scalability and fast random access. Different prediction modesare designed to fit MVV with different correlations andmeet different requirements of the Multi-view video coding (MVC). An optimal prediction mode is adaptively selected from the candidate modes according to the correlation characteristics of MVV. Experimental results haveproved that MMVC not only has best random accessibility, but also has outstanding performance in compressioneffciency, low memory requirement, low complexity andview scalability. MMVC is regarded as the most effcientand balanced MVC scheme among the compared schemes.