A Computer-Assisted Colorization Approach Based on Efficient Belief Propagation and Graph Matching

Region-based approaches have been proposed to computer-assisted colorization problem, typically using shape similarity and topology relations between regions. Given a colored frame, the objective is to automatically colorize consecutive frames, minimizing the user effort to colorize the remaining regions. We propose a new colorization algorithm based on graph matching, using Belief Propagation to explore the spatial relations between sites through Markov Random Fields. Each frame is represented by a graph with each region being associated to a vertex. A colored frame is chosen as a `model' and the colors are propagated to uncolored frames by computing a correspondence between regions, exploring the spatial relations between vertices, considering three types of information: adjacency, distance and orientation. Experiments are shown in order to demonstrate the importance of the spatial relations when comparing two graphs with strong deformations and with `topological' differences.