5 research outputs found

    Determining the Optical Flow Using Wavelet Coefficients

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    The optical flow (OF) can be used to perform motion-based segmentation or 3D reconstruction. Many techniques have been developed to estimate the OF. Some approaches are based on global assumptions; others deal with local information. ALthough OF has been studied for more than one decade, reducing the estimation error is still a difficult problem. Generally, algorithms to determine the OF are based on an equation, which links the gradient components of the luminance signal, so as to impose its invariance over time. Therefore, to determine the OF, it is usually necessary to calculate the gradient components in space and time. A new way to approximate this gradient information from a spatio- temporal wavelet decomposition is proposed here. In other words, assuming that the luminance information of the video sequences be represented in a multiresolution structure for compression or transmission purposes, we propose to estimate the luminance gradient components directly from the coefficients of the wavelet transform. Using a multiresolution formalism, we provide a way to estimate the motion field at different resolution levels. OF estimates obtained at low resolution can be projected at higher resolution levels so as to improve the robustness of the estimation to noise and to better locate the flow discontinuities, while remaining computationally efficient. Results are shown for both synthetic and real-world sequences, comparing it with a non multiresolution approach

    PDSRS: An attribute based approach for multimedia data storage and retrieval

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    Texture Retrieval with Linguistic Descriptions

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