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This document presents a novel feature points tracking algorithm that integrates inertial measurement unit (IMU) data to enhance the accuracy and efficiency of monocular visual-inertial systems (VINS). The proposed IMU-aided feature points tracking (IFPT) method utilizes a preintegration-based predictor and a variable-sized search window for local matching, addressing issues of false matches and feature point overlap. Experimental results demonstrate the effectiveness of the algorithm compared to traditiona

Author

prabhatsoni18999

Language

EN