All Outputs (8)

Back to Butterworth - a Fourier Basis for 3D Surface Relief Hole Filling within RGB-D Imagery (2016)
Presentation / Conference Contribution
Atapour-Abarghouei, A., de La Garanderie, G. P., & Breckon, T. P. (2016, December). Back to Butterworth - a Fourier Basis for 3D Surface Relief Hole Filling within RGB-D Imagery. Presented at 2016 23rd International Conference on Pattern Recognition (ICPR), Cancun

We address the problem of hole filling in RGB-D (color and depth) images, obtained from either active or stereo based sensing, for the purposes of object removal and missing depth estimation. This is performed independently on the low frequency depth... Read More about Back to Butterworth - a Fourier Basis for 3D Surface Relief Hole Filling within RGB-D Imagery.

Transfer Learning Using Convolutional Neural Networks For Object Classification Within X-Ray Baggage Security Imagery (2016)
Presentation / Conference Contribution
Akcay, S., Kundegorski, M., Devereux, M., & Breckon, T. (2016, September). Transfer Learning Using Convolutional Neural Networks For Object Classification Within X-Ray Baggage Security Imagery. Presented at 2016 IEEE International Conference on Image Processing., Phoenix, AZ, USA

We consider the use of transfer learning, via the use of deep Convolutional Neural Networks (CNN) for the image classification problem posed within the context of X-ray baggage security screening. The use of a deep multi-layer CNN approach, tradition... Read More about Transfer Learning Using Convolutional Neural Networks For Object Classification Within X-Ray Baggage Security Imagery.

Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow (2016)
Presentation / Conference Contribution
Hamilton, O., & Breckon, T. (2016, September). Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow. Presented at 2016 IEEE International Conference on Image Processing., Phoenix, AZ, USA

Mapping an ever changing urban environment is a challenging task as we are generally interested in mapping the static scene and not the dynamic objects, such as cars and people. We propose a novel approach to the problem of dynamic object removal wit... Read More about Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow.

SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder (2016)
Presentation / Conference Contribution
Al Moubayed, N., Breckon, T., Matthews, P., & McGough, A. (2016, August). SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder

In This paper we present a novel approach to spam filtering and demonstrate its applicability with respect to SMS messages. Our approach requires minimum features engineering and a small set of labelled data samples. Features are extracted using topi... Read More about SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder.

Quantitative Evaluation of Stereo Visual Odometry for Autonomous Vessel Localisation in Inland Waterway Sensing Applications (2015)
Journal Article
Kriechbaumer, T., Blackburn, K., Breckon, T., Hamilton, O., & Riva-Casado, M. (2015). Quantitative Evaluation of Stereo Visual Odometry for Autonomous Vessel Localisation in Inland Waterway Sensing Applications. Sensors, 15(12), 31869-31887. https://doi.org/10.3390/s151229892

Autonomous survey vessels can increase the efficiency and availability of wide-area river environment surveying as a tool for environment protection and conservation. A key challenge is the accurate localisation of the vessel, where bank-side vegetat... Read More about Quantitative Evaluation of Stereo Visual Odometry for Autonomous Vessel Localisation in Inland Waterway Sensing Applications.

Robust visual tracking via speedup multiple kernel ridge regression (2015)
Journal Article
Qian, C., Breckon, T. P., & Li, H. (2015). Robust visual tracking via speedup multiple kernel ridge regression. Journal of Electronic Imaging, 24(5), Article 053016. https://doi.org/10.1117/1.jei.24.5.053016

Most of the tracking methods attempt to build up feature spaces to represent the appearance of a target. However, limited by the complex structure of the distribution of features, the feature spaces constructed in a linear manner cannot characterize... Read More about Robust visual tracking via speedup multiple kernel ridge regression.

A Photogrammetric Approach for Real-time 3D Localization and Tracking of Pedestrians in Monocular Infrared Imagery (2014)
Presentation / Conference Contribution
Kundegorski, M., & Breckon, T. (2014, October). A Photogrammetric Approach for Real-time 3D Localization and Tracking of Pedestrians in Monocular Infrared Imagery. Presented at Proc. SPIE Optics and Photonics for Counterterrorism, Crime Fighting and Defence

Target tracking within conventional video imagery poses a significant challenge that is increasingly being addressed via complex algorithmic solutions. The complexity of this problem can be fundamentally attributed to the ambiguity associated with ac... Read More about A Photogrammetric Approach for Real-time 3D Localization and Tracking of Pedestrians in Monocular Infrared Imagery.

Improved Depth Recovery In Consumer Depth Cameras via Disparity Space Fusion within Cross-spectral Stereo (2014)
Presentation / Conference Contribution
Payen de La Garanderie, G., & Breckon, T. (2014, September). Improved Depth Recovery In Consumer Depth Cameras via Disparity Space Fusion within Cross-spectral Stereo. Presented at Proceedings of the British Machine Vision Conference

We address the issue of improving depth coverage in consumer depth cameras based on the combined use of cross-spectral stereo and near infra-red structured light sensing. Specifically we show that fusion of disparity over these modalities, within the... Read More about Improved Depth Recovery In Consumer Depth Cameras via Disparity Space Fusion within Cross-spectral Stereo.