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[Wavelet] surf DL : 0: This is achieved by relying on integral images for image convolutions by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a distribution-based descriptor) and by simplifying these methods to the essential. This leads to a combination of novel detection, description, and matching steps. The paper presents experimental results on a standard uation set, as well as on imagery obtained in the context of a real-life object recognition application. Both show SURF’s strong performance. -This is achieved by relying on integral images for image convolutions by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a distribution-based descriptor) and by simplifying these methods to the essential. This leads to a combination of novel detection, description, and matching steps. The paper presents experimental results on a standard uation set, as well as on imagery obtained in the context of a real-life object recognition application. Both show SURF’s strong performance.
Date : 2025-12-14 Size : 665kb User : Amal