Scene-Adaptive Switching of Segmentation Methods for Object-Based Video Encoding

摘要

In order to create efficient object-based video encoding, the authors have proposed a scene-adaptive region segmentation method that can work with a variety of different types of scenes. In their method, encoding efficiency is improved by adaptively selecting for each frame the optimal method from among several different region segmentation methods determined using Bayesian decision-making based on the video features of a scene. In this paper, the authors describe the Bayesian decision and training methods, and then formalize the image features and the different region segmentation methods. Finally, the authors demonstrate the validity of the proposed approach through experiments.