Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Controlled animation of video sprites
Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models
The Journal of Machine Learning Research
Gaussian Process Dynamical Models for Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Video texture is a new type of medium which can provide a continuous, infinitely varying stream of video images from a recorded video clip. It can be synthesized by rearranging the order of frames based on the similarities between all pairs of frames. In this paper, we propose a new method for generating video textures by implementing probabilistic principal components analysis (PPCA) and Gaussian Process Dynamical model (GPDM). Compared to the original video texture technique, video texture synthesized by PPCA and GPDM has the following advantages: it might generate new video frames that have never existed in the input video clip before; the problem of "dead-end" is totally avoided; it could also provide video textures that are more robust to noise.