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• W2068293430 startingPage "47" @default.
• W2068293430 abstract "This paper presents a model-based object recognition approach that uses a Gabor wavelet representation. The key idea is to use magnitude, phase, and frequency measures of the Gabor wavelet representation in an innovative flexible matching approach that can provide robust recognition. The Gabor grid, a topology-preserving map, efficiently encodes both signal energy and structural information of an object in a sparse multiresolution representation. The Gabor grid subsamples the Gabor wavelet decomposition of an object model and is deformed to allow the indexed object model match with similar representation obtained using image data. Flexible matching between the model and the image minimizes a cost function based on local similarity and geometric distortion of the Gabor grid. Grid erosion and repairing is performed whenever a collapsed grid, due to object occlusion, is detected. The results on infrared imagery are presented, where objects undergo rotation, translation, scale, occlusion, and aspect variations under changing environmental conditions." @default.
• W2068293430 created "2016-06-24" @default.
• W2068293430 creator A5061869604 @default.
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• W2068293430 date "1997-01-01" @default.
• W2068293430 modified "2023-09-27" @default.
• W2068293430 title "Gabor wavelet representation for 3-D object recognition" @default.
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• W2068293430 doi "https://doi.org/10.1109/83.552096" @default.
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