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Titlebook: Computer Vision - ECCV 2008; 10th European Confer David Forsyth,Philip Torr,Andrew Zisserman Conference proceedings 2008 Springer-Verlag Be

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Syed Ahmed Ali,Shahzad Memon,Nisar Memon on the same problem, the method starts by averaging aligned foreground regions of a walking pedestrian to produce a representation of motion and shape (known as a .) that has some immunity to noise in foreground segmentations and phase of the walking cycle. Our key novelty is for carried objects to
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https://doi.org/10.1007/978-3-642-28589-9oothing penalty on the camera trajectory. The smoothing parameter, usually fixed by trial and error, is automatically estimated using Cross-Validation. This technique is extremely expensive in its basic form. We derive Gauss-Newton Cross-Validation, which closely approximates Cross-Validation, while
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Statistics for Industry and Technologyconsider the manifold of invariant planar contours and learn the low-dimensional submanifold corresponding to the object contours by observing the object off-line from a number of different viewpoints. This submanifold of object contours can be parametrized by the view sphere and, in turn, be used f
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