A unified approach to segmentation and categorization of dynamic textures
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Dynamic texture analysis and segmentation using deterministic partially self-avoiding walks
Expert Systems with Applications: An International Journal
Dynamic texture segmentation based on deterministic partially self-avoiding walks
Computer Vision and Image Understanding
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We propose a dynamic texture feature-based algorithm for registering two video sequences of a rigid or nonrigid scene taken from two synchronous or asynchronous cameras. We model each video sequence as the output of a linear dynamical system, and transform the task of registering frames of the two sequences to that of registering the parameters of the corresponding models. This allows us to perform registration using the more classical image-based features as opposed to space-time features, such as space-time volumes or feature trajectories. As the model parameters are not uniquely defined, we propose a generic method to resolve these ambiguities by jointly identifying the parameters from multiple video sequences. We finally test our algorithm on a wide variety of challenging video sequences and show that it matches the performance of significantly more computationally expensive existing methods.