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Dandan Luo

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Proceedings Article | 11 October 2023 Paper

Semantic object assisted loop closure detection for indoor UAV

Lin Wang, Bo Jiang, Hong Xu, Dandan Luo

Proceedings Volume 12800, 128006I (2023) https://doi.org/10.1117/12.3004093

KEYWORDS: Semantics, Unmanned aerial vehicles, Visualization, Detection and tracking algorithms, Target detection, Image processing

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Loop closure detection is an important means to reduce the accumulated errors in visual SLAM (Simultaneous Localization and Mapping) systems. The change in the viewpoint of a UAV (Unmanned Air Vehicle) while navigating autonomously using SLAM poses a great challenge for loop closure detection. Compared to traditional appearance features, objects are a high-level semantic information that can be easily observed from different viewpoints. In this paper, a semantic object assisted loop closure detection method is proposed for indoor UAV. Firstly, the image color histogram and object histogram are used to initially filter and sort the loop closure candidate frames. Then, the spatial relationship of objects is described by semantic topology graph, and the semantic nodes are described by semantic histogram. Finally, the bag-of-words model and graph matching are combined for the verification of loop closure detection to achieve accurate and robust loop closure detection. Experiments on publicly available data show that the method in this paper has better precision and recall compared with other classical methods.

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