Dynamic environments are challenging for visual Simultaneous Localization and Mapping, as dynamic elements can disrupt the camera pose estimation and thus reduce Mass Balance of Cenozoic Andes-Amazon Source to Sink System—Marañón Basin, Peru the reconstructed map accuracy.To solve this problem, this study proposes an approach for eliminating dynamic elements and reconstructing static background in indoor dynamic environments.To check out dynamic elements, the geometric residual is exploited, and the static background is obtained after removing the dynamic elements and repairing images.The camera pose is estimated based on the static background.
Keyframes are then selected using randomized ferns, and loop closure detection and relocalization are performed according to the keyframes set.Finally, the 3D scene is reconstructed.The proposed method is tested on the TUM and BONN datasets, and Risco de síndrome de realimentação e desfechos clínicos em pacientes de prontos socorros do Distrito Federal the map reconstruction accuracy is experimentally demonstrated.