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Video segmentation is a crucial pass to content-based video summarization and retrieval. In this paper, we present a practical method to efficiently group video content into semantic segments. First we detect shots with double-threshold method to find raw shots quickly, followed by redundant frames removal though spatial color distribution to get the key frames. Finally, we cluster the key frames...
This paper proposed an algorithm using Bayesian on-line learning for object based video image segmentation. First the strengths of image pixel's spatial location, color and motion segments are weighted and then unified in one framework for image clustering and segmentation. Here, the appropriate modeling of probability distribution functions (PDF) of each feature cluster is obtained through Gaussian...
Describes a method for learning classes of facial motion patterns from a video of a human interacting with a computerized embodied agent. The method also learns correlations between the discovered motion classes and the current interaction context. Our work is motivated by two hypotheses. First, a computer user's facial displays are context-dependent, especially in the presence of an embodied agent...
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