Transferring color to greyscale images
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
The Journal of Machine Learning Research
Semi-Supervised Learning on Riemannian Manifolds
Machine Learning
A Statistical Approach to Texture Classification from Single Images
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
Image Manifolds which are Isometric to Euclidean Space
Journal of Mathematical Imaging and Vision
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Bayesian Hierarchical Model for Learning Natural Scene Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
ACM SIGGRAPH 2006 Papers
Learning Nonlinear Image Manifolds by Global Alignment of Local Linear Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Manifold learning for natural image sets
Manifold learning for natural image sets
Color to Gray: Visual Cue Preservation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized sparse metric learning with relative comparisons
Knowledge and Information Systems
Distance approximation techniques to reduce the dimensionality for multimedia databases
Knowledge and Information Systems
Mining historical manuscripts with local color patches
Knowledge and Information Systems
Learning colours from textures by sparse manifold embedding
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Ensemble Manifold Regularization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sparse transfer learning for interactive video search reranking
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
DAML: Domain Adaptation Metric Learning
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
MatchSim: a novel similarity measure based on maximum neighborhood matching
Knowledge and Information Systems
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The capability of inferring colours from the texture (grayscale contents) of an image is useful in many application areas, when the imaging device/environment is limited. Traditional manual or limited automatic colour assignment involves intensive human effort. In this paper, we have developed a user-friendly colourisation technique, where the algorithm learns the relation between textures and colours in a user-provided example image and applies the relation to predict the colours in the target image. The key contribution of the proposed technique is trifold. First, we have explicitly built a linear model for the texture-colour relation. Second, we have considered the global non-linear structure of the data distribution by applying the linear model locally; and the local area is determined automatically by sparsity constraints. Third, we have introduced semantic information to further improve the colourisation. Examples demonstrate the effectiveness of the proposed techniques. Moreover, we have conducted a subjective study, where user experience supports the superiority of our method over existing techniques.