SLAM algorithm based on bounding box and deep continuity in dynamic scene Online publication date: Mon, 21-Mar-2022
by Baofu Fang; Xiumeng Han; Zaijun Wang; Xiaohui Yuan
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 21, No. 4, 2021
Abstract: To solve the problems of low positioning accuracy and poor robustness caused by the inability of Simultaneous Localisation and Mapping (SLAM) algorithm to deal with dynamic targets in dynamic scenes, a SLAM algorithm based on bounding box and depth continuity in dynamic scenes is proposed. Firstly, the pixel random search filling process is carried out in combination with the depth and the bounding box to obtain the pixel-level segmentation result of the prior dynamic target. Then, the dynamic features are screened to eliminate the influence of dynamic targets. According to the screening results, relative static features which can be used for posture optimisation are selected. Posture optimisation is carried out by combining the static features to obtain the optimised camera posture. All experimental results show that the proposed algorithm significantly improves the positioning accuracy and real-time performance of SLAM algorithm in complex dynamic scenes.
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