Linear Object Classes and Image Synthesis From a Single Example Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
A Generative Method for Textured Motion: Analysis and Synthesis
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Automatic Construction of Active Appearance Models as an Image Coding Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic shape and appearance modeling via moving and deforming layers
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
A model change detection approach to dynamic scene modeling
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
The dynamic textures for water synthesis based on statistical modeling
Edutainment'07 Proceedings of the 2nd international conference on Technologies for e-learning and digital entertainment
Stereo vision based motion parameter estimation
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Space-time spectral model for object detection in dynamic textured background
Pattern Recognition Letters
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We propose a model of the joint variation of shape and appearance of portions of an image sequence. The model is conditionally linear, and can be thought of as an extension of active appearance models to exploit the temporal correlation of adjacent image frames. Inference of the model parameters can be performed efficiently using established numerical optimization techniques borrowed from finite-element analysis and system identification techniques.