no code implementations • 8 Mar 2024 • Maria Waheed, Michael Milford, Xiaojun Zhai, Maria Fasli, Klaus McDonald-Maier, Shoaib Ehsan
Voting is an extremely relevant topic to explore in terms of its application and significance for any ensemble VPR setup.
no code implementations • 16 Jan 2024 • Bruno Arcanjo, Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
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.
no code implementations • 20 Dec 2023 • Bruno Arcanjo, Bruno Ferrarini, Maria Fasli, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
Visual place recognition (VPR) enables autonomous systems to localize themselves within an environment using image information.
no code implementations • 14 Dec 2023 • Oliver Grainge, Michael Milford, Indu Bodala, Sarvapali D. Ramchurn, Shoaib Ehsan
This has resulted in methods that use deep learning models too large to deploy on low powered edge devices.
no code implementations • 9 May 2023 • Bruno Arcanjo, Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
Visual place recognition (VPR) enables autonomous systems to localize themselves within an environment using image information.
no code implementations • 9 May 2023 • Maria Waheed, Michael Milford, Xiaojun Zhai, Klaus McDonald-Maier, Shoaib Ehsan
We aim to determine whether a single optimal voting scheme exists or, much like in other fields of research, the selection of a voting technique is relative to its application and environment.
no code implementations • 9 May 2023 • Mihnea-Alexandru Tomita, Bruno Ferrarini, Michael Milford, Klaus McDonald-Maier, Shoaib Ehsan
Images incorporate a wealth of information from a robot's surroundings.
no code implementations • 24 Mar 2023 • Bruno Arcanjo, Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
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.
no code implementations • 1 Mar 2023 • Maria Waheed, Sania Waheed, Michael Milford, Klaus McDonald-Maier, Shoaib Ehsan
The proposed, Switch-Fuse system, is an interesting way to combine both the robustness of switching VPR techniques based on complementarity and the force of fusing the carefully selected techniques to significantly improve performance.
no code implementations • 26 Feb 2023 • Mihnea-Alexandru Tomita, Bruno Ferrarini, Michael Milford, Klaus McDonald-Maier, Shoaib Ehsan
The sequence length that enables 100% place matching performance is reported and an analysis of the amount of data required for each VPR technique to perform the transfer on the entire spectrum of JPEG compression is provided.
no code implementations • 3 Oct 2022 • Bruno Arcanjo, Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
Low-overhead visual place recognition (VPR) is a highly active research topic.
no code implementations • 17 Sep 2022 • Mihnea-Alexandru Tomita, Bruno Ferrarini, Michael Milford, Klaus McDonald-Maier, Shoaib Ehsan
Moreover, this paper demonstrates how fine-tuning a CNN can be utilised as an optimisation method for JPEG compressed data to perform more consistently with the image transformations detected in extremely JPEG compressed images.
no code implementations • 1 Mar 2022 • Maria Waheed, Michael Milford, Klaus McDonald-Maier, Shoaib Ehsan
This innovative use of multiple VPR techniques allow our system to be more efficient and robust than other combined VPR approaches employing brute force and running multiple VPR techniques at once.
no code implementations • 24 Feb 2022 • Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
In a typical BNN, the first convolution is not completely binarized for the sake of accuracy.
no code implementations • 5 Jan 2022 • Eduardo Weber Wachter, Server Kasap, Sefki Kolozali, Xiaojun Zhai, Shoaib Ehsan, Klaus McDonald-Maier
A few types of radiation like Total Ionizing Dose (TID) effects often cause permanent damages on such nanoscale electronic devices, and current state-of-the-art technologies to tackle TID make use of expensive radiation-hardened devices.
no code implementations • 22 Sep 2021 • Bruno Arcanjo, Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
In this work, our goal is to provide an algorithm of extreme compactness and efficiency while achieving state-of-the-art robustness to appearance changes and small point-of-view variations.
no code implementations • 22 Sep 2021 • Rose Power, Mubariz Zaffar, Bruno Ferrarini, Michael Milford, Klaus McDonald-Maier, Shoaib Ehsan
(4) How does the performance of a high-end platform relate to an on-board low-end embedded platform for VPR?
no code implementations • 2 Mar 2021 • Mihnea-Alexandru Tomită, Mubariz Zaffar, Michael Milford, Klaus McDonald-Maier, Shoaib Ehsan
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?
no code implementations • 25 Feb 2021 • William H. B. Smith, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
The second contribution is an algorithm `DMC' that combines our scene classification with distance and memorability for visual mapping.
no code implementations • 16 Feb 2021 • Maria Waheed, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
Visual place recognition (VPR) is the problem of recognising a previously visited location using visual information.
1 code implementation • 1 Oct 2020 • Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
To the best of our knowledge, this is the first attempt to propose binary neural networks for solving the visual place recognition problem effectively under changing conditions and with significantly reduced resource requirements.
no code implementations • 28 Sep 2020 • Mihnea-Alexandru Tomită, Mubariz Zaffar, Michael Milford, Klaus McDonald-Maier, Shoaib Ehsan
In this paper, we present a new handcrafted VPR technique that achieves state-of-the-art place matching performance under challenging conditions.
1 code implementation • 17 May 2020 • Mubariz Zaffar, Sourav Garg, Michael Milford, Julian Kooij, David Flynn, Klaus McDonald-Maier, Shoaib Ehsan
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.
no code implementations • 18 Sep 2019 • Ahmad Khaliq, Shoaib Ehsan, Michael Milford, Klaus McDonald-Maier
In the last few years, Deep Convolutional Neural Networks (D-CNNs) have shown state-of-the-art (SOTA) performance for Visual Place Recognition (VPR), a pivotal component of long-term intelligent robotic vision (vision-aware localization and navigation systems).
no code implementations • 1 Aug 2019 • Bruno Ferrarini, Maria Waheed, Sania Waheed, Shoaib Ehsan, Michael Milford, Klaus D. McDonald-Maier
Visual Place Recognition (VPR) is a fundamental yet challenging task for small Unmanned Aerial Vehicle (UAV).
1 code implementation • 3 May 2019 • Grigorios Kalliatakis, Shoaib Ehsan, Maria Fasli, Klaus McDonald-Maier
Every year millions of men, women and children are forced to leave their homes and seek refuge from wars, human rights violations, persecution, and natural disasters.
no code implementations • 16 Apr 2019 • Mubariz Zaffar, Ahmad Khaliq, Shoaib Ehsan, Michael Milford, Kostas Alexis, Klaus McDonald-Maier
Visual Place Recognition (VPR) has seen significant advances at the frontiers of matching performance and computational superiority over the past few years.
no code implementations • 9 Apr 2019 • Bruno Ferrarini, Shoaib Ehsan, Adrien Bartoli, Aleš Leonardis, Klaus D. McDonald-Maier
This paper aims to fill this gap and proposes two experimental scenarios to assess the tolerance to imbalanced training data and to determine the generalization performance of a model with unfamiliar affine transformations of the images.
no code implementations • 21 Mar 2019 • Mubariz Zaffar, Ahmad Khaliq, Shoaib Ehsan, Michael Milford, Klaus McDonald-Maier
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.
no code implementations • 11 Feb 2019 • Grigorios Kalliatakis, Shoaib Ehsan, Maria Fasli, Klaus D. McDonald-Maier
Our hypothesis is that the emotional state of a person -- how positive or pleasant an emotion is, and the control level of the situation by the person -- are powerful cues for perceiving potential human rights violations.
no code implementations • 8 Nov 2018 • Mubariz Zaffar, Shoaib Ehsan, Michael Milford, Klaus Mcdonald Maier
This paper presents a cognition-inspired agnostic framework for building a map for Visual Place Recognition.
1 code implementation • 7 Nov 2018 • Ahmad Khaliq, Shoaib Ehsan, Zetao Chen, Michael Milford, Klaus McDonald-Maier
This paper presents a lightweight visual place recognition approach, capable of achieving high performance with low computational cost, and feasible for mobile robotics under significant viewpoint and appearance changes.
no code implementations • 1 Aug 2018 • Jose Carlos Villarreal Guerra, Zeba Khanam, Shoaib Ehsan, Rustam Stolkin, Klaus McDonald-Maier
Weather conditions often disrupt the proper functioning of transportation systems.
1 code implementation • 5 Jul 2018 • Somdip Dey, Grigorios Kalliatakis, Sangeet Saha, Amit Kumar Singh, Shoaib Ehsan, Klaus McDonald-Maier
Intelligent Transportation Systems (ITS) have become an important pillar in modern "smart city" framework which demands intelligent involvement of machines.
no code implementations • 4 Jul 2018 • Mubariz Zaffar, Shoaib Ehsan, Rustam Stolkin, Klaus McDonald Maier
Simultaneous Localization and Mapping, commonly known as SLAM, has been an active research area in the field of Robotics over the past three decades.
1 code implementation • 12 May 2018 • Grigorios Kalliatakis, Shoaib Ehsan, Ales Leonardis, Klaus McDonald-Maier
With this, we show that HRA database poses a challenge at a higher level for the well studied representation learning methods, and provide a benchmark in the task of human rights violations recognition in visual context.
no code implementations • 9 Nov 2017 • Grigorios Kalliatakis, Anca Sticlaru, George Stamatiadis, Shoaib Ehsan, Ales Leonardis, Juergen Gall, Klaus D. McDonald-Maier
We question the dominant role of real-world training images in the field of material classification by investigating whether synthesized data can generalise more effectively than real-world data.
no code implementations • 24 Sep 2017 • Bruno Ferrarini, Shoaib Ehsan, Ales Leonardis, Naveed Ur Rehman, Klaus D. McDonald-Maier
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.
no code implementations • 30 Mar 2017 • Grigorios Kalliatakis, Shoaib Ehsan, Klaus D. McDonald-Maier
The growing presence of devices carrying digital cameras, such as mobile phones and tablets, combined with ever improving internet networks have enabled ordinary citizens, victims of human rights abuse, and participants in armed conflicts, protests, and disaster situations to capture and share via social media networks images and videos of specific events.
no code implementations • 12 Mar 2017 • Grigorios Kalliatakis, Shoaib Ehsan, Maria Fasli, Ales Leonardis, Juergen Gall, Klaus D. McDonald-Maier
We conduct a rigorous evaluation on a common ground by combining this dataset with different state-of-the-art deep convolutional architectures in order to achieve recognition of human rights violations.
no code implementations • 12 Mar 2017 • Grigorios Kalliatakis, Georgios Stamatiadis, Shoaib Ehsan, Ales Leonardis, Juergen Gall, Anca Sticlaru, Klaus D. McDonald-Maier
Determining the material category of a surface from an image is a demanding task in perception that is drawing increasing attention.
no code implementations • 19 May 2016 • Shoaib Ehsan, Adrian F. Clark, Ales Leonardis, Naveed Ur Rehman, Klaus D. McDonald-Maier
Since local feature detection has been one of the most active research areas in computer vision during the last decade, a large number of detectors have been proposed.
no code implementations • 19 May 2016 • Bruno Ferrarini, Shoaib Ehsan, Naveed Ur Rehman, Ales Leonardis, Klaus D. McDonald-Maier
The efficiency and the good accuracy in determining the optimal feature detector for any operating condition, make the proposed tool suitable to be utilized in real visual applications.
no code implementations • 17 Oct 2015 • Shoaib Ehsan, Adrian F. Clark, Wah M. Cheung, Arjunsingh M. Bais, Bayar I. Menzat, Nadia Kanwal, Klaus D. McDonald-Maier
In embedded vision systems, parallel computation of the integral image presents several design challenges in terms of hardware resources, speed and power consumption.
no code implementations • 17 Oct 2015 • Shoaib Ehsan, Adrian F. Clark, Klaus D. McDonald-Maier
Different detector pairs and triplets are examined quantitatively and the results provide a useful guideline for combining detectors in applications that require a reasonable spatial distribution of image features.
no code implementations • 17 Oct 2015 • Shoaib Ehsan, Adrian F. Clark, Bruno Ferrarini, Naveed Ur Rehman, Klaus D. McDonald-Maier
Since local feature detection has been one of the most active research areas in computer vision, a large number of detectors have been proposed.
no code implementations • 17 Oct 2015 • Bruno Ferrarini, Shoaib Ehsan, Naveed Ur Rehman, Klaus D. McDonald-Maier
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.
no code implementations • 17 Oct 2015 • Shoaib Ehsan, Adrian F. Clark, Naveed Ur Rehman, Klaus D. McDonald-Maier
Addressing the storage problem of integral image in embedded vision systems, the paper presents two algorithms which allow substantial decrease (at least 44. 44%) in the memory requirements.
no code implementations • 29 Apr 2015 • Shoaib Ehsan, Adrian F. Clark, Klaus D. McDonald-Maier
Scale- and rotation-invariant local feature extraction is a low level computer vision task with very high computational complexity.
no code implementations • 29 Apr 2015 • Shoaib Ehsan, Klaus D. McDonald-Maier
This paper also introduces a novel method to achieve integral image word length reduction for SURF detector.
no code implementations • 29 Apr 2015 • Shoaib Ehsan, Nadia Kanwal, Adrian F. Clark, Klaus D. McDonald-Maier
The most frequently employed measure for performance characterisation of local feature detectors is repeatability, but it has been observed that this does not necessarily mirror actual performance.
no code implementations • 27 Apr 2015 • Shoaib Ehsan, Klaus D. McDonald-Maier
Research in the last decade has highlighted the potential of vision sensing in this regard.