Semantic Object-level Modeling for Robust Visual Camera Relocalization Article Swipe

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Yifan Zhu , Lingjuan Miao , Haitao Wu , Zhiqiang Zhou , Weiyi Chen , Longwen Wu ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2402.06951

Visual relocalization is crucial for autonomous visual localization and navigation of mobile robotics. Due to the improvement of CNN-based object detection algorithm, the robustness of visual relocalization is greatly enhanced especially in viewpoints where classical methods fail. However, ellipsoids (quadrics) generated by axis-aligned object detection may limit the accuracy of the object-level representation and degenerate the performance of visual relocalization system. In this paper, we propose a novel method of automatic object-level voxel modeling for accurate ellipsoidal representations of objects. As for visual relocalization, we design a better pose optimization strategy for camera pose recovery, to fully utilize the projection characteristics of 2D fitted ellipses and the 3D accurate ellipsoids. All of these modules are entirely intergrated into visual SLAM system. Experimental results show that our semantic object-level mapping and object-based visual relocalization methods significantly enhance the performance of visual relocalization in terms of robustness to new viewpoints.

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Computer Vision

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Computer vision Computer science Artificial intelligence Object (grammar) Computer graphics (images)

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2402.06951
PDF: https://arxiv.org/pdf/2402.06951
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4391871678

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DOI: https://doi.org/10.48550/arxiv.2402.06951

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Title: Semantic Object-level Modeling for Robust Visual Camera Relocalization

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Type: preprint

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Language: en

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Publication year: 2024

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Publication date: 2024-02-10

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Authors: Yifan Zhu, Lingjuan Miao, Haitao Wu, Zhiqiang Zhou, Weiyi Chen, Longwen Wu

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Landing page: https://arxiv.org/abs/2402.06951

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PDF URL: https://arxiv.org/pdf/2402.06951

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OA URL: https://arxiv.org/pdf/2402.06951

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Concepts: Computer vision, Computer science, Artificial intelligence, Object (grammar), Computer graphics (images)

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