Computer analysis of regular repetitive textures
Proceedings of a workshop on Image understanding workshop
Extracting periodicity of a regular texture based on autocorrelation functions
Pattern Recognition Letters
Detecting, localizing and grouping repeated scene elements from an image
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Geometric Grouping of Repeated Elements within Images
Shape, Contour and Grouping in Computer Vision
A Computational Model for Periodic Pattern Perception Based on Frieze and Wallpaper Groups
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstructing Occluded Surfaces Using Synthetic Apertures: Stereo, Focus and Robust Measures
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Space-Time Completion of Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Regular Texture Analysis as Statistical Model Selection
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Deformed Lattice Discovery Via Efficient Mean-Shift Belief Propagation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Discovering texture regularity as a higher-order correspondence problem
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Region filling and object removal by exemplar-based image inpainting
IEEE Transactions on Image Processing
Automatic restoration of corrupted regions in images using object width transform
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
Hi-index | 0.00 |
We introduce a novel image defencing method suitable for consumer photography, where plausible results must be achieved under common camera settings. First, detection of lattices with see-through texels is performed in an iterative process using online learning and classification from intermediate results to aid subsequent detection. Then, segmentation of the foreground is performed using accumulated statistics from all lattice points. Next, multi-view inpainting is performed to fill in occluded areas with information from shifted views where parts of the occluded regions may be visible. For regions occluded in all views, we use novel symmetry-augmented inpainting, which combines traditional texture synthesis with an increased pool of candidate patches found by simulating bilateral symmetry patterns from the source image. The results show the effectiveness of our proposed method.