Active shape models—their training and application
Computer Vision and Image Understanding
Photomosaics
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
EP '98/RIDT '98 Proceedings of the 7th International Conference on Electronic Publishing, Held Jointly with the 4th International Conference on Raster Imaging and Digital Typography: Electronic Publishing, Artistic Imaging, and Digital Typography
A bootstrapping algorithm for learning linear models of object classes
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
ACM SIGGRAPH 2003 Papers
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Textureshop: texture synthesis as a photograph editing tool
ACM SIGGRAPH 2004 Papers
Shape Matching and Object Recognition Using Low Distortion Correspondences
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
ACM SIGGRAPH 2006 Papers
ACM SIGGRAPH 2006 Papers
GI '07 Proceedings of Graphics Interface 2007
Coordinates for instant image cloning
ACM SIGGRAPH 2009 papers
Sketch2Photo: internet image montage
ACM SIGGRAPH Asia 2009 papers
ACM SIGGRAPH Asia 2009 papers
ACM SIGGRAPH 2010 papers
EGSR'06 Proceedings of the 17th Eurographics conference on Rendering Techniques
Accurate and discernible photocollages
CAe '12 Proceedings of the Eighth Annual Symposium on Computational Aesthetics in Graphics, Visualization, and Imaging
Digital Camouflage Images Using Two-scale Decomposition
Computer Graphics Forum
| Hi-index | 0.00 |
A hidden image is a form of artistic expression in which one or more secondary objects (or scenes) are hidden within a primary image. Features of the primary image, especially its edges and texture, are used to portray a secondary object. People can recognize both the primary and secondary intent in such pictures, although the time taken to do so depends on the prior experience of the viewer and the strength of the clues. Here, we present a system for creating such images. It relies on the ability of human perception to recognize an object, e.g. a human face, from incomplete edge information within its interior, rather than its outline. Our system detects edges of the object to be hidden, and then finds a place where it can be embedded within the scene, together with a suitable transformation for doing so, by optimizing an energy based on edge differences. Embedding is performed using a modified Poisson blending approach, which strengthens matched edges of the host image using edges of the object being embedded. We show various hidden images generated by our system.