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Titlebook: Computer Vision -- ECCV 2014; 13th European Confer David Fleet,Tomas Pajdla,Tinne Tuytelaars Conference proceedings 2014 Springer Internati

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Spectral Clustering with a Convex Regularizer on Millions of Images mild conditions the local convergence rate is . where . is the number of iterations; further, our analysis shows that the convergence improves linearly by increasing the number of threads. We give extensive experimental results on a range of vision datasets demonstrating the algorithm’s empirical behavior.
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,Treachery: March 1896–16 October 1897,mage collections are significantly different. The performance of the proposed framework is demonstrated on four challenging datasets in terms of 4-d modeling accuracy as well as quantitative evaluation of 3-d change detection.
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https://doi.org/10.1007/b138386such as: weak frame-proposals containing unexpected events, action recognition, motion saliency. Illustrative results indicate that motion prediction is not only feasible, but also provides valuable information for a number of applications.
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https://doi.org/10.1007/b138386 is high. In this article, we propose a method that can estimate the normal component of high velocity optical flow using only the local image values in each single frame. The equation used for estimating the normal velocity is theoretically derived and the condition the equation holds is also revealed.
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