SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
Pyramid-based texture analysis/synthesis
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Minimax entropy principle and its application to texture modeling
Neural Computation
Approximate and probabilistic algorithms for shading and rendering structured particle systems
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Texture Mixing and Texture Movie Synthesis Using Statistical Learning
IEEE Transactions on Visualization and Computer Graphics
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Graphcut textures: image and video synthesis using graph cuts
ACM SIGGRAPH 2003 Papers
Flow-based video synthesis and editing
ACM SIGGRAPH 2004 Papers
Analysis and Synthesis of Textured Motion: Particles and Waves
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
Dynamic Shape and Appearance Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
A model validation approach to texture recognition and inpainting
Pattern Recognition
Dynamic texture synthesis using a spatial temporal descriptor
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A fast temporal texture synthesis algorithm using segment genetic algorithm
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Dynamic texture analysis and synthesis using tensor decomposition
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part II
Non linear temporal textures synthesis: a monte carlo approach
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
An evolution computation based approach to synthesize video texture
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part II
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Natural scenes contain rich stochastic motion patterns which are characterized by the movement of a large number of small elements, such as falling snow, raining, flying birds, firework and waterfall. In this paper, we call these motion patterns textured motion and present a generative method that combines statistical models and algorithms from both texture and motion analysis. The generative method includes the following three aspects. 1). Photometrically, an image is represented as a superposition of linear bases in atomic decomposition using an overcomplete dictionary, such as Gabor or Laplacian. Such base representation is known to be generic for natural images, and it is low dimensional as the number of bases is often 100 times smaller than the number of pixels. 2). Geometrically, each moving element (called moveton), such as the individual snowflake and bird, is represented by a deformable template which is a group of several spatially adjacent bases. Such templates are learned through clustering. 3). Dynamically, the movetons are tracked through the image sequence by a stochastic algorithm maximizing a posterior probability. A classic second order Markov chain model is adopted for the motion dynamics. The sources and sinks of the movetons are modeled by birth and death maps. We adopt an EM-like stochastic gradient algorithm for inference of the hidden variables: bases, movetons, birth/death maps, parameters of the dynamics. The learned models are also verified through synthesizing random textured motion sequences which bear similar visual appearance with the observed sequences.