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- W2205399681 abstract "This chapter presents a new method for feature extraction in unsupervised motion segmentation of image sequences. The method is based on the multichannel filtering of the input image sequence using adapted gabor filters. The chapter uses the histogram of a quantized two-dimensional parameter space resulting from a three dimensional orientation analysis to select the main Gabor filter parameters namely azimuthal and elevational angle. The three-dimensional orientation analysis consists essentially of the eigenvalue and eigenvector computations of inertia tensors in the three dimensional frequency spaces. The feature images are obtained from the complex valued filtered sequences using a simple magnitude computation, and they are subsequently evaluated employing a multichannel segmentation algorithm. The performance of the algorithm is demonstrated using two segmentation examples that are based on artificial as well as real image sequences." @default.
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- W2205399681 title "Unsupervised Motion Segmentation of Image Sequences using Adaptive Filtering" @default.
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- W2205399681 doi "https://doi.org/10.1016/b978-044482587-2/50099-9" @default.
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