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Titlebook: Computer Vision -- ECCV 2010; 11th European Confer Kostas Daniilidis,Petros Maragos,Nikos Paragios Conference proceedings 2010 Springer-Ver

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楼主: crusade
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Desire in Pre-modern Spiritual Directionmages and videos on common datasets are provided in order to demonstrate the relevant speedup and the increased localization accuracy with respect to sliding window strategy using a pedestrian classifier based on covariance descriptors and a cascade of Logitboost classifiers.
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Desire in Pre-modern Spiritual Directiontly developed unsupervised learning methods as well as by taking advantage of the local spatial coherence of the output labels. We show that our method works reliably on two challenging urban datasets that are an order of magnitude larger than what was used to evaluate previous approaches.
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https://doi.org/10.1057/9780230375727 accuracy when compared to the state-of-the-art 2D detectors and (b) gives a 3D interpretation of the location of the object, derived from a 2D image. We evaluate the detector on beds, for which we give extensive quantitative results derived from images of real scenes.
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Explicit computations of spectra,pair of input frames. We also use our model to extract low-level motion features in a multi-stage architecture for action recognition, demonstrating competitive performance on both the KTH and Hollywood2 datasets.
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Desire in Pre-modern Spiritual Directionn improves performance even when classifiers are based on the same feature or feature combination. These two extensions result in significantly improved performance over the state-of-the-art on two challenging datasets.
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Problems of Protection and Security,truly isotropic. We show the significance of removing the directional bias in the computation of the cost in certain applications of fast marching method. We also compare the accuracy and computation times of our proposed methods with the existing state of the art fast marching techniques to demonstrate the superiority of our method.
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