Multiple-Kernel Local-Patch Descriptor
Arun Mukundan, Giorgos Tolias, Ondrej Chum

TL;DR
This paper introduces a novel local-patch descriptor that combines multiple kernels to improve robustness against patch misregistration, outperforming existing methods on benchmark tests.
Contribution
It presents a new multiple-kernel descriptor based on efficient match kernels of patch gradients, integrating two parametrizations for enhanced robustness.
Findings
Outperforms state-of-the-art methods on local patch benchmarks
Combines polar and Cartesian parametrizations for robustness
Effective against patch mis-registration and orientation noise
Abstract
We propose a multiple-kernel local-patch descriptor based on efficient match kernels of patch gradients. It combines two parametrizations of gradient position and direction, each parametrization provides robustness to a different type of patch miss-registration: polar parametrization for noise in the patch dominant orientation detection, Cartesian for imprecise location of the feature point. Even though handcrafted, the proposed method consistently outperforms the state-of-the-art methods on two local patch benchmarks.
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Taxonomy
TopicsAdvanced Image and Video Retrieval Techniques · Robotics and Sensor-Based Localization · Image Processing Techniques and Applications
