IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Threshold selection by clustering gray levels of boundary
Pattern Recognition Letters
Human facial illustrations: Creation and psychophysical evaluation
ACM Transactions on Graphics (TOG)
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer-Generated Papercutting
PG '07 Proceedings of the 15th Pacific Conference on Computer Graphics and Applications
NPAR '08 Proceedings of the 6th international symposium on Non-photorealistic animation and rendering
A Hierarchical Compositional Model for Face Representation and Sketching
IEEE Transactions on Pattern Analysis and Machine Intelligence
An automatic portrait system based on and-or graph representation
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
Portrait painting using active templates
Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Non-Photorealistic Animation and Rendering
Style and abstraction in portrait sketching
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Artistic minimal rendering with lines and blocks
Graphical Models
eHeritage of shadow puppetry: creation and manipulation
Proceedings of the 21st ACM international conference on Multimedia
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This paper presents a method to render artistic paper-cut of human portraits. Rendering paper-cut images from photographs can be considered as an inhomogeneous image binarization problem, to which ideal solutions should reproduce vivid image details with sparse cuts. Especially for portrait paper-cut, good artworks should capture impressive facial features. To achieve this goal, our approach integrates bottom-up and top-down cues to better determine the binary values. In the bottom-up phase, facial components are localized on the input photograph, and their draft binary versions are proposed. In the top-down phase, we use pre-collected representative paper-cut templates, with which we synthesize the final paper-cut image by matching them with the bottom-up proposals. Experimental results show that our approach can produce visually satisfactory results.