Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
The problems of computer-assisted animation
SIGGRAPH '78 Proceedings of the 5th annual conference on Computer graphics and interactive techniques
Graphical models for graph matching: Approximate models and optimal algorithms
Pattern Recognition Letters - Special issue: In memoriam Azriel Rosenfeld
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Structural Matching of 2D Electrophoresis Gels using Graph Models
SIBGRAPI '08 Proceedings of the 2008 XXI Brazilian Symposium on Computer Graphics and Image Processing
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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.