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http://dx.doi.org/10.7746/jkros.2022.17.3.334

Semantic Visual Place Recognition in Dynamic Urban Environment  

Arshad, Saba (Control and Robot Engineering, Chungbuk National University)
Kim, Gon-Woo (Department of Intelligent Systems and Robotics, Chungbuk National University)
Publication Information
The Journal of Korea Robotics Society / v.17, no.3, 2022 , pp. 334-338 More about this Journal
Abstract
In visual simultaneous localization and mapping (vSLAM), the correct recognition of a place benefits in relocalization and improved map accuracy. However, its performance is significantly affected by the environmental conditions such as variation in light, viewpoints, seasons, and presence of dynamic objects. This research addresses the problem of feature occlusion caused by interference of dynamic objects leading to the poor performance of visual place recognition algorithm. To overcome the aforementioned problem, this research analyzes the role of scene semantics in correct detection of a place in challenging environments and presents a semantics aided visual place recognition method. Semantics being invariant to viewpoint changes and dynamic environment can improve the overall performance of the place matching method. The proposed method is evaluated on the two benchmark datasets with dynamic environment and seasonal changes. Experimental results show the improved performance of the visual place recognition method for vSLAM.
Keywords
Semantics; Simultaneous Localization and Mapping; Visual Place Recognition;
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