TicTacToon: a paperless system for professional 2D animation
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
NPAR '02 Proceedings of the 2nd international symposium on Non-photorealistic animation and rendering
Computer-assisted cel animation: post-processing after inbetweening
Proceedings of the 1st international conference on Computer graphics and interactive techniques in Australasia and South East Asia
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
SIAM Journal on Scientific Computing
Efficient Shape Matching Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
DBSC-based animation enhanced with feature and motion: Research Articles
Computer Animation and Virtual Worlds - CASA 2006
Integral Invariants for Shape Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive dimension reduction using discriminant analysis and K-means clustering
Proceedings of the 24th international conference on Machine learning
Patch Alignment for Dimensionality Reduction
IEEE Transactions on Knowledge and Data Engineering
Manifold elastic net: a unified framework for sparse dimension reduction
Data Mining and Knowledge Discovery
Beyond search: Event-driven summarization for web videos
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Towards a Relevant and Diverse Search of Social Images
IEEE Transactions on Multimedia
Assistive tagging: A survey of multimedia tagging with human-computer joint exploration
ACM Computing Surveys (CSUR)
Complex Object Correspondence Construction in Two-Dimensional Animation
IEEE Transactions on Image Processing
Pairwise constraints based multiview features fusion for scene classification
Pattern Recognition
IEEE MultiMedia
Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research
Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research
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In 2D animation, it is a tedious task and time-consuming that drawing in-betweens for the animator. Correspondence construction between two key frames is a necessary condition for auto-inbetween in the computer animation auxiliary system. In this paper, we combine patch alignment framework (PAF) with the idea of sparse coding for correspondence construction. Specifically, local patches construction can have a large impact on the accuracy of correspondence. Therefore, in our framework, in order to construct local patches in each point on an object and align these patches in a new feature space, we adopt sparse coding instead of k-nearest neighbor method in patch construction. The correspondences between two objects can be detected by subsequent clustering method. This approach can efficiently improves the performance of correspondence construction. To optimize the proposed framework, we use least angle regression (LARS) method to overcome the slow operating efficiency problem of lasso. Experimental results on our cartoon data set which is built on industrial production suggest the advanced accuracy of correspondence construction in our improved framework, and is even better than the framework of using k-nearest neighbor algorithm to construct local patches.