Search Results for author:
Found 10 papers, 1 papers with code
On the Estimation of Image-matching Uncertainty in Visual Place Recognition
In Visual Place Recognition (VPR) the pose of a query image is estimated by comparing the image to a map of reference images with known reference poses.
CoPR: Towards Accurate Visual Localization With Continuous Place-descriptor Regression
Firstly, the reference images for VPR are only available at sparse poses in a map, which enforces an upper bound on the maximum achievable localization accuracy through VPR.
A Benchmark Comparison of Visual Place Recognition Techniques for Resource-Constrained Embedded Platforms
(4) How does the performance of a high-end platform relate to an on-board low-end embedded platform for VPR?
Sequence-Based Filtering for Visual Route-Based Navigation: Analysing the Benefits, Trade-offs and Design Choices
This raises a number of interesting research questions: How does performance boost (due to sequential filtering) vary along the entire spectrum of single-frame-based matching methods?
ConvSequential-SLAM: A Sequence-based, Training-less Visual Place Recognition Technique for Changing Environments
In this paper, we present a new handcrafted VPR technique that achieves state-of-the-art place matching performance under challenging conditions.
VPR-Bench: An Open-Source Visual Place Recognition Evaluation Framework with Quantifiable Viewpoint and Appearance Change
Visual Place Recognition (VPR) is the process of recognising a previously visited place using visual information, often under varying appearance conditions and viewpoint changes and with computational constraints.
Are State-of-the-art Visual Place Recognition Techniques any Good for Aerial Robotics?
Visual Place Recognition (VPR) has seen significant advances at the frontiers of matching performance and computational superiority over the past few years.
Levelling the Playing Field: A Comprehensive Comparison of Visual Place Recognition Approaches under Changing Conditions
In recent years there has been significant improvement in the capability of Visual Place Recognition (VPR) methods, building on the success of both hand-crafted and learnt visual features, temporal filtering and usage of semantic scene information.
Memorable Maps: A Framework for Re-defining Places in Visual Place Recognition
This paper presents a cognition-inspired agnostic framework for building a map for Visual Place Recognition.
Sensors, SLAM and Long-term Autonomy: A Review
Simultaneous Localization and Mapping, commonly known as SLAM, has been an active research area in the field of Robotics over the past three decades.
