Exploring Emerging Trends and Research Opportunities in Visual Place Recognition

Antonios Gasteratos, Konstantinos A. Tsintotas, Tobias Fischer, Yiannis Aloimonos, Michael Milford
11/18/2024
cs.CVcs.RO

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Abstract

Visual-based recognition, e.g., image classification, object detection, etc., is a long-standing challenge in computer vision and robotics communities. Concerning the roboticists, since the knowledge of the environment is a prerequisite for complex navigation tasks, visual place recognition is vital for most localization implementations or re-localization and loop closure detection pipelines within simultaneous localization and mapping (SLAM). More specifically, it corresponds to the system's ability to identify and match a previously visited location using computer vision tools. Towards developing novel techniques with enhanced accuracy and robustness, while motivated by the success presented in natural language processing methods, researchers have recently turned their attention to vision-language models, which integrate visual and textual data.

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@article{gasteratos2024exploring,
  title  = {Exploring Emerging Trends and Research Opportunities in Visual Place Recognition},
  author = {Antonios Gasteratos and Konstantinos A. Tsintotas and Tobias Fischer and Yiannis Aloimonos and Michael Milford},
  year   = {2024},
  eprint = {2411.11481},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2411.11481v1}
}

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