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Feature-based visual simultaneous localization and mapping (SLAM) is an effective localization approach for robots in unknown environments. Classic handcrafted features perform well in 2D image matching tasks. However, in the tracking task of SLAM, the region at the edge of the object in the image is often unstable because of the lack of spatial information. In this paper, we refer to the features at the edge of the object as edge-features and propose an effective method to process thedoi:10.1109/access.2020.3013806 fatcat:mitmhnefenbbdovgjjjrcdhibm