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Advances in computer vision and image processing technology have led to great success in image recognition when the images are clear. However, in real-world applications, images are often blurred due to factors such as atmospheric turbulence, object-camera relative motion, and focus. This imposes a great challenge on practical image recognition tasks. To improve the performance of burred image recognition,...
This paper proposes a novel local feature descriptor, called a local feature statistics histogram (LFSH), for efficient 3D point cloud registration. An LFSH forms a comprehensive description of local shape geometries by encoding their statistical properties on local depth, point density, and angles between normals. The sub-features in the LFSH descriptor are low-dimensional and quite efficient to...
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