Mr. Changshe Ma Profile

Changshe Ma

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Proceedings Article | 21 December 2023 Paper

A visual place recognition method based on semantic instance and bag context

Ruitang Wang, Changshe Ma

Proceedings Volume 12970, 129702C (2023) https://doi.org/10.1117/12.3012485

KEYWORDS: Semantics, Visualization, Image segmentation, Deep learning, Object detection, Light sources and illumination, Binary data, Detection and tracking algorithms, Associative arrays, Visual process modeling

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Visual place recognition is an essential function for robot system, which can effectively reduce position error via traversing same place. However, a major challenge in this field is to be robust against viewpoint and illumination changes caused by environmental variations. To solve this problem, we propose a novel visual place recognition method in coarse-to-fine manner, which incorporating both high-level semantic feature and bag context information. Firstly, the semantic features of an image are obtained by adopting deep learning network, which converts the image data to the instance representation in more simple way. In coarse stage, we utilize the Bag of word (BoW) model to quantify semantic features by calculating their frequency distribution. In fine stage, we enhance the spatial correlations of semantic objects to further distinguish similar scenes. Through the above two stage, we achieve a robust pipeline of visual place recognition to tackle viewpoint and condition variations. Experimental results on several datasets, including both indoor scenes and outdoor scenes, show that our method achieve good performance, especially for extreme conditions.

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