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Image-only place recognition based on regional aggregating ConvNet features for underground parking lots

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Abstract

Place recognition searches the closest map node to the query node, which is an important task for vehicle localization. Traditional visual place recognition methods for underground parking lots require the deployment of additional location signals, such as WiFi, Bluetooth. This paper utilizes only front-view images to realize place recognition. First, we employ a random coefficient to reduce the dimensionality of the ConvNet features to obtain the CCFs (Condense ConvNet Features). Second, we average the CCFs of a regional zone to obtain the RACF (Regional Aggregating ConvNet Feature). Compared with WiFi, Bluetooth, RACF is extracted from the front-view image and has a superior ability to represent regional zones. Third, we propose a multiscale place recognition method that adopts a coarse-to-fine strategy that greatly reduces time consumption and accelerates precision. Finally, we evaluate the proposed method on the data collected in the underground parking lot of Hubei University of Technology. The experimental results illustrate that the proposed method has high precision with a fast speed.

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Acknowledgments

This work presented in this paper was funded by the National Natural Science Foundation of China (61502155), the National Natural Science Foundation of China (61772180), the Project of Xiangyang Research Institute of Hubei University of Technology (No. XYYJ2022C08), Fujian Provincial Key Laboratory of Data intensive Computing and Key Laboratory of intelligent Computing and information Processing, Fujian: BD201801.

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Authors and Affiliations

  1. School of Computer Science, Hubei University of Technology, 28 Nanli Road, Hongshan District, Wuhan City, Hubei, China

    Xianglong Wang, Xinyuan Zhu, Zhongzhen Yan, Zhiwei Ye, Jiangyi Du, Zhigang Xu & Chun Liu

  2. Electric Engineering Corporation Limited, China Railway Seventh Group Corporation Limited, Yingxie Road, Zhengzhou, China

    Feng Guo

  3. Baokang Public Security Bureau, No.110 Qingxi Road, Baokang City, Xiangyang, Hubei, China

    Cailu Mao

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  1. Xianglong Wang
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  2. Xinyuan Zhu
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  4. Zhiwei Ye
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Correspondence to Zhigang Xu.

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Wang, X., Zhu, X., Yan, Z. et al. Image-only place recognition based on regional aggregating ConvNet features for underground parking lots. Vis Comput 40, 1167–1177 (2024). https://doi.org/10.1007/s00371-023-02838-6

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