Shadow removal for local feature detector and descriptor learning using a camera sensor sensitivity model
摘要:
Training a descriptor network includes obtaining a first image of a scene from an image capture device, applying a sensor sensitivity model to the first image to obtain shadow-invariant image data for the first image, and selecting a first patch from the image. Training a descriptor network also includes obtaining a subset of the shadow-invariant image data corresponding to the first patch, and training the descriptor network to provide localization data based on the first patch and the subset of the shadow-invariant image data.
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