MURAL - Maynooth University Research Archive Library

    Place Recognition in Challenging Conditions

    Ramachandran, Saravanabalagi and McDonald, John (2019) Place Recognition in Challenging Conditions. In: Irish Machine Vision and Image Processing Conference, 28-30 August 2019, Technological University Dublin. (In Press)

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    Place recognition in a visual SLAM system helps build and maintain a map from multiple traversals of the same environment while closing loops to correct drift accumulated over time. Despite the marked success in visual place recognition research over the past decade, it remains a challenging problem in the context of variations caused due to different times of the day, weather, lighting and seasons. In this paper, we address this problem by progressively training convolutional neural networks in a siamese fashion to generate embeddings that encode semantic and visual features for sequence-aligned image pairs taken at different timescales and viewpoints. We demonstrate the robustness of the approach using Freiburg visual place recognition benchmark dataset consisting of aligned outdoor image sequences taken over extended time periods that include the variations mentioned above.

    Item Type: Conference or Workshop Item (Poster)
    Keywords: Place Recognition; Deep Learning; Image Embeddings;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 10987
    Depositing User: John McDonald
    Date Deposited: 23 Aug 2019 16:27
    Refereed: Yes
    Funders: Science Foundation Ireland
      Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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