28 citations · 37 across the 18 of their papers we have counts for
20 papers
Image-based Geo-localization for Robotics: Are Black-box Vision-Language Models there yet?
Sania Waheed, Bruno Ferrarini, Michael Milford +2
The advances in Vision-Language models (VLMs) offer exciting opportunities for robotic applications involving image geo-localization - the problem of identifying the geo-coordinate…
On Motion Blur and Deblurring in Visual Place Recognition
Timur Ismagilov, Bruno Ferrarini, Michael Milford +3
Visual Place Recognition (VPR) in mobile robotics enables robots to localize themselves by recognizing previously visited locations using visual data. While the reliability of VPR…
Multi-Technique Sequential Information Consistency For Dynamic Visual Place Recognition In Changing Environments
Bruno Arcanjo, Bruno Ferrarini, Michael Milford +2
Visual place recognition (VPR) is an essential component of robot navigation and localization systems that allows them to identify a place using only image data. VPR is challenging…
Aggregating Multiple Bio-Inspired Image Region Classifiers For Effective And Lightweight Visual Place Recognition
Bruno Arcanjo, Bruno Ferrarini, Maria Fasli +3
Visual place recognition (VPR) enables autonomous systems to localize themselves within an environment using image information. While VPR techniques built upon a Convolutional Neur…
Visual Place Recognition with Low-Resolution Images
Mihnea-Alexandru Tomita, Bruno Ferrarini, Michael Milford +2
Images incorporate a wealth of information from a robot's surroundings. With the widespread availability of compact cameras, visual information has become increasingly popular for…
Patch-DrosoNet: Classifying Image Partitions With Fly-Inspired Models For Lightweight Visual Place Recognition
Bruno Arcanjo, Bruno Ferrarini, Michael Milford +2
Visual place recognition (VPR) enables autonomous systems to localize themselves within an environment using image information. While Convolution Neural Networks (CNNs) currently d…
A-MuSIC: An Adaptive Ensemble System For Visual Place Recognition In Changing Environments
Bruno Arcanjo, Bruno Ferrarini, Michael Milford +2
Visual place recognition (VPR) is an essential component of robot navigation and localization systems that allows them to identify a place using only image data. VPR is challenging…
Data-Efficient Sequence-Based Visual Place Recognition with Highly Compressed JPEG Images
Mihnea-Alexandru Tomita, Bruno Ferrarini, Michael Milford +2
Visual Place Recognition (VPR) is a fundamental task that allows a robotic platform to successfully localise itself in the environment. For decentralised VPR applications where the…
Merging Classification Predictions with Sequential Information for Lightweight Visual Place Recognition in Changing Environments
Bruno Arcanjo, Bruno Ferrarini, Michael Milford +2
Low-overhead visual place recognition (VPR) is a highly active research topic. Mobile robotics applications often operate under low-end hardware, and even more hardware capable sys…
Data Efficient Visual Place Recognition Using Extremely JPEG-Compressed Images
Mihnea-Alexandru Tomita, Bruno Ferrarini, Michael Milford +2
Visual Place Recognition (VPR) is the ability of a robotic platform to correctly interpret visual stimuli from its on-board cameras in order to determine whether it is currently lo…
Highly-Efficient Binary Neural Networks for Visual Place Recognition
Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier +1
VPR is a fundamental task for autonomous navigation as it enables a robot to localize itself in the workspace when a known location is detected. Although accuracy is an essential r…
A Benchmark Comparison of Visual Place Recognition Techniques for Resource-Constrained Embedded Platforms
Rose Power, Mubariz Zaffar, Bruno Ferrarini +3
Visual Place Recognition (VPR) has been a subject of significant research over the last 15 to 20 years. VPR is a fundamental task for autonomous navigation as it enables self-local…
An Efficient and Scalable Collection of Fly-inspired Voting Units for Visual Place Recognition in Changing Environments
Bruno Arcanjo, Bruno Ferrarini, Michael Milford +2
State-of-the-art visual place recognition performance is currently being achieved utilizing deep learning based approaches. Despite the recent efforts in designing lightweight conv…
Binary Neural Networks for Memory-Efficient and Effective Visual Place Recognition in Changing Environments
Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier +1
Visual place recognition (VPR) is a robot's ability to determine whether a place was visited before using visual data. While conventional hand-crafted methods for VPR fail under ex…
Visual Place Recognition for Aerial Robotics: Exploring Accuracy-Computation Trade-off for Local Image Descriptors
Bruno Ferrarini, Maria Waheed, Sania Waheed +3
Visual Place Recognition (VPR) is a fundamental yet challenging task for small Unmanned Aerial Vehicle (UAV). The core reasons are the extreme viewpoint changes, and limited comput…
Assessing Capsule Networks With Biased Data
Bruno Ferrarini, Shoaib Ehsan, Adrien Bartoli +2
Machine learning based methods achieves impressive results in object classification and detection. Utilizing representative data of the visual world during the training phase is cr…
Performance Characterization of Image Feature Detectors in Relation to the Scene Content Utilizing a Large Image Database
Bruno Ferrarini, Shoaib Ehsan, Ales Leonardis +2
Selecting the most suitable local invariant feature detector for a particular application has rendered the task of evaluating feature detectors a critical issue in vision research.…
Automatic Selection of the Optimal Local Feature Detector
Bruno Ferrarini, Shoaib Ehsan, Naveed Ur Rehman +2
A large number of different feature detectors has been proposed so far. Any existing approach presents strengths and weaknesses, which make a detector optimal only for a limited ra…
Performance Characterization of Image Feature Detectors in Relation to the Scene Content Utilizing a Large Image Database
Bruno Ferrarini, Shoaib Ehsan, Naveed Ur Rehman +1
Selecting the most suitable local invariant feature detector for a particular application has rendered the task of evaluating feature detectors a critical issue in vision research.…
Assessing The Performance Bounds Of Local Feature Detectors: Taking Inspiration From Electronics Design Practices
Shoaib Ehsan, Adrian F. Clark, Bruno Ferrarini +2
Since local feature detection has been one of the most active research areas in computer vision, a large number of detectors have been proposed. This has rendered the task of chara…