Abstract
To address the problem of feature information redundancy caused by visual simultaneous localization and mapping algorithm with point and line features in high-texture environment, a fast simultaneous localization and mapping algorithm with point and line feature based on image entropy is proposed. In this paper, we first propose a new feature extraction strategy, which determines the parameters of the feature extractor by image entropy; then, the idea of weighting is introduced in pose estimation, and the point and line features are weighted by the image entropy; finally, we test our method using the KITTI and EuRoC dataset, and demonstrate that our method improves the real-time performance of the system while ensuring the accuracy and robustness of the system.
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