Image Repairing: Robust Image Synthesis by Adaptive ND Tensor Voting IEEE Computer Society Conference on Computer Vision and Pattern Recognition Jiaya Jia, Chi-Keung Tang Jiaya Jia, Chi-Keung Tang Computer Science Computer Science Department Department The Hong Kong University of The Hong Kong University of Science and Technology Science and Technology
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Image Repairing: Robust Image Synthesis by Adaptive N D Tensor Voting
Image Repairing: Robust Image Synthesis by Adaptive N D Tensor Voting. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Jiaya Jia, Chi-Keung Tang Computer Science Department The Hong Kong University of Science and Technology. Motivation. - PowerPoint PPT Presentation
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Image Repairing: Robust Image Synthesis by Adaptive ND Tensor Voting
IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Computer Science DepartmentComputer Science DepartmentThe Hong Kong University of The Hong Kong University of
Science and TechnologyScience and Technology
Motivation
• Main difficulties to repair a severely damaged image of natural scene– Mixture of texture and colors– Inhomogeneity of patterns– Regular object shapes
Motivation
• Given as few as one image without additional knowledge, we address:– How much color and shape information in the
existing part is needed to seamlessly fill the hole?– How good can we achieve in order to reduce
possible visual artifact when the information available is not sufficient.
• Robust Tensor Voting method is adopted
Tensor Voting Review• Tensors: compact representation of information • Tensor encoding:
3D tensor
3
1 2Ball tensor: uncertainty
in all directions
Plate tensor: certainty of directions in a plate
Stick tensor: certainty along two opposite directions
Tensor Voting Review
• Voting process is to propagate local information
P
Osculating circle
Image repairing system
Input Damaged Image
Texture-based Segmentation
Statistical Region Merging
Curve Connection
Adaptive Scale Selection
NND Tensor Voting
Output Repaired Image
Complete Segmentation
Image synthesis
SegmentationSegmentation
• JSEG [Deng and Manjunath 2001] – color quantization – spatial segmentation
• Mean shift [Comanicu and Meer 2002]
• Deterministic Annealing Framework [Hofmann et al 1998]