Probabilistic Visual Place Recognition for Hierarchical Localization

Abstract

Visual localization techniques often comprise a hierarchical localization pipeline, with a visual place recognition module used as a coarse localizer to initialize a pose refinement stage. While improving the pose refinement step has been the focus of much recent research, most work on the coarse localization stage has focused on improvements like increased invariance to appearance change, without improving what can be loose error tolerances. In this letter, we propose two methods which adapt image retrieval techniques used for visual place recognition to the Bayesian state estimation formulation for localization. We demonstrate significant improvements to the localization accuracy of the coarse localization stage using our methods, whilst retaining state-of-the-art performance under severe appearance change. Using extensive experimentation on the Oxford RobotCar dataset, results show that our approach outperforms comparable state-of-the-art methods in terms of precision-recall performance for localizing image sequences. In addition, our proposed methods provides the flexibility to contextually scale localization latency in order to achieve these improvements. The improved initial localization estimate opens up the possibility of both improved overall localization performance and modified pose refinement techniques that leverage this improved spatial prior.

arXiv comment8 pages, 4 figures, RA-L standalone

References in corpus (9)

• ORB-SLAM: a Versatile and Accurate Monocular SLAM System
• On the Performance of ConvNet Features for Place Recognition
• Multi-Process Fusion: Visual Place Recognition Using Multiple Image Processing Methods
• D2-Net: A Trainable CNN for Joint Detection and Description of Local Features
• Single-View Place Recognition under Seasonal Changes
• Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset
• Leveraging Deep Visual Descriptors for Hierarchical Efficient Localization
• Condition-Invariant Multi-View Place Recognition
• Scalable Place Recognition Under Appearance Change for Autonomous Driving

Cited by in corpus (8)

• The Revisiting Problem in Simultaneous Localization and Mapping: A Survey on Visual Loop Closure Detection
• Applications of Spiking Neural Networks in Visual Place Recognition
• Probabilistic Appearance-Invariant Topometric Localization with New Place Awareness
• Sparse Semantic Map-Based Monocular Localization in Traffic Scenes Using Learned 2D-3D Point-Line Correspondences
• Improving Visual Place Recognition Based Robot Navigation By Verifying Localization Estimates
• EDTformer: An Efficient Decoder Transformer for Visual Place Recognition
• SelaVPR++: Towards Seamless Adaptation of Foundation Models for Efficient Place Recognition
• SciceVPR: Stable Cross-Image Correlation Enhanced Model for Visual Place Recognition