Outputs (204)

Experimentally Defined Convolutional Neural Network Architecture Variants for Non-temporal Real-time Fire Detection (2018)
Presentation / Conference Contribution
Dunnings, A., & Breckon, T. (2018, October). Experimentally Defined Convolutional Neural Network Architecture Variants for Non-temporal Real-time Fire Detection. Presented at 25th IEEE International Conference on Image Processing (ICIP)., Athens, Greece

In this work we investigate the automatic detection of fire pixel regions in video (or still) imagery within real-time bounds without reliance on temporal scene information. As an extension to prior work in the field, we consider the performance of e... Read More about Experimentally Defined Convolutional Neural Network Architecture Variants for Non-temporal Real-time Fire Detection.

Eliminating the Dreaded Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery (2018)
Presentation / Conference Contribution
Payen de La Garanderie, G., Atapour-Abarghouei, A., & Breckon, T. (2018, September). Eliminating the Dreaded Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery. Presented at 15th European Conference on Computer Vision (ECCV 2018), Munich, Germany

Recent automotive vision work has focused almost exclusively on processing forward-facing cameras. However, future autonomous vehicles will not be viable without a more comprehensive surround sensing, akin to a human driver, as can be provided by 360... Read More about Eliminating the Dreaded Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery.

On the Impact of Parallax Free Colour and Infrared Image Co-Registration to Fused Illumination Invariant Adaptive Background Modelling (2018)
Presentation / Conference Contribution
Loveday, M., & Breckon, T. (2018, June). On the Impact of Parallax Free Colour and Infrared Image Co-Registration to Fused Illumination Invariant Adaptive Background Modelling. Presented at Computer Vision and Pattern Recognition Workshops (CVPR) 2018., Salt Lake City, Utah, USA

Real-time Low-Cost Omni-directional Stereo Vision via Bi-Polar Spherical Cameras (2018)
Presentation / Conference Contribution
Lin, K., & Breckon, T. (2018, June). Real-time Low-Cost Omni-directional Stereo Vision via Bi-Polar Spherical Cameras. Presented at 15th International Conference on Image Analysis and Recognition (ICIAR 2018)., Póvoa de Varzim, Portugal

With the rise of consumer-grade spherical cameras, offering full omni-directional 360∘ image capture, the potential for low-cost omni-directional stereo vision is ever present. Whilst this potentially offers novel low-cost omni-directional depth sens... Read More about Real-time Low-Cost Omni-directional Stereo Vision via Bi-Polar Spherical Cameras.

Encoding Stereoscopic Depth Features for Scene Understanding in Off-Road Environments (2018)
Presentation / Conference Contribution
Holder, C., & Breckon, T. (2018, June). Encoding Stereoscopic Depth Features for Scene Understanding in Off-Road Environments. Presented at 15th International Conference on Image Analysis and Recognition (ICIAR 2018)., Póvoa de Varzim, Portugal

Extended Patch Prioritization for Depth Filling Within Constrained Exemplar-Based RGB-D Image Completion (2018)
Presentation / Conference Contribution
Atapour-Abarghouei, A., & Breckon, T. P. (2018, December). Extended Patch Prioritization for Depth Filling Within Constrained Exemplar-Based RGB-D Image Completion. Presented at International Conference Image Analysis and Recognition, Póvoa de Varzim, Portugal

We address the problem of hole filling in depth images, obtained from either active or stereo sensing, for the purposes of depth image completion in an exemplar-based framework. Most existing exemplar-based inpainting techniques, designed for color i... Read More about Extended Patch Prioritization for Depth Filling Within Constrained Exemplar-Based RGB-D Image Completion.

On the Impact of Illumination-Invariant Image Pre-transformation on Contemporary Automotive Semantic Scene Understanding (2018)
Presentation / Conference Contribution
Alshammari, N., Akcay, S., & Breckon, T. (2018, June). On the Impact of Illumination-Invariant Image Pre-transformation on Contemporary Automotive Semantic Scene Understanding. Presented at The 29th IEEE Intelligent Vehicles Symposium (IEEE IV 2018)., Changshu, China

Extended Patch Prioritization For Depth Hole Filling Within Constrained Exemplar-Based RGB-D Image Completion (2018)
Presentation / Conference Contribution
Atapour-Abarghouei, A., & Breckon, T. (2018, June). Extended Patch Prioritization For Depth Hole Filling Within Constrained Exemplar-Based RGB-D Image Completion. Presented at 15th International Conference on Image Analysis and Recognition (ICIAR 2018)., Póvoa de Varzim, Portugal

Using Deep Convolutional Neural Network Architectures for Object Classification and Detection within X-ray Baggage Security Imagery (2018)
Journal Article
Akcay, S., Kundegorski, M., Willcocks, C., & Breckon, T. (2018). Using Deep Convolutional Neural Network Architectures for Object Classification and Detection within X-ray Baggage Security Imagery. IEEE Transactions on Information Forensics and Security, 13(9), 2203-2215. https://doi.org/10.1109/tifs.2018.2812196

We consider the use of deep Convolutional Neural Networks (CNN) with transfer learning for the image classification and detection problems posed within the context of X-ray baggage security imagery. The use of the CNN approach requires large amounts... Read More about Using Deep Convolutional Neural Network Architectures for Object Classification and Detection within X-ray Baggage Security Imagery.

A Comparative Review of Plausible Hole Filling Strategies in the Context of Scene Depth Image Completion (2018)
Journal Article
Atapour-Abarghouei, A., & Breckon, T. (2018). A Comparative Review of Plausible Hole Filling Strategies in the Context of Scene Depth Image Completion. Computers and Graphics, 72, 39-58. https://doi.org/10.1016/j.cag.2018.02.001

Despite significant research focus on 3D scene capture systems, numerous unresolved challenges remain in relation to achieving full coverage scene depth estimation which is the key part of any modern 3D sensing system. This has created an area of res... Read More about A Comparative Review of Plausible Hole Filling Strategies in the Context of Scene Depth Image Completion.