Outputs (205)

Lost in Compression: the Impact of Lossy Image Compression on Variable Size Object Detection within Infrared Imagery (2022)
Presentation / Conference Contribution
Bhowmik, N., Barker, J., Gaus, Y., & Breckon, T. (2022, June). Lost in Compression: the Impact of Lossy Image Compression on Variable Size Object Detection within Infrared Imagery. Presented at 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), New Orleans, Louisiana

Lossy image compression strategies allow for more efficient storage and transmission of data by encoding data to a reduced form. This is essential enable training with larger datasets on less storage-equipped environments. However, such compression c... Read More about Lost in Compression: the Impact of Lossy Image Compression on Variable Size Object Detection within Infrared Imagery.

Cross-modal Image Synthesis in Dual-Energy X-Ray Security Imagery (2022)
Presentation / Conference Contribution
Isaac-Medina, B., Bhowmik, N., Willcocks, C., & Breckon, T. (2022, June). Cross-modal Image Synthesis in Dual-Energy X-Ray Security Imagery. Presented at 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), New Orleans, Louisiana

Dual-energy X-ray scanners are used for aviation security screening given their capability to discriminate materials inside passenger baggage. To facilitate manual operator inspection, a pseudo-colouring is assigned to the effective composition of th... Read More about Cross-modal Image Synthesis in Dual-Energy X-Ray Security Imagery.

Measuring Hidden Bias within Face Recognition via Racial Phenotypes (2022)
Presentation / Conference Contribution
Yucer, S., Tekras, F., Al Moubayed, N., & Breckon, T. (2022, January). Measuring Hidden Bias within Face Recognition via Racial Phenotypes. Presented at Proc. Winter Conference on Applications of Computer Vision, Waikoloa, HI

Recent work reports disparate performance for intersectional racial groups across face recognition tasks: face verification and identification. However, the definition of those racial groups has a significant impact on the underlying findings of such... Read More about Measuring Hidden Bias within Face Recognition via Racial Phenotypes.

Semi-Supervised Surface Anomaly Detection of Composite Wind Turbine Blades From Drone Imagery (2022)
Presentation / Conference Contribution
Barker, J., Bhowmik, N., & Breckon, T. (2022, February). Semi-Supervised Surface Anomaly Detection of Composite Wind Turbine Blades From Drone Imagery. Presented at Computer Vision Theory and Applications 2022

Within commercial wind energy generation, the monitoring and predictive maintenance of wind turbine blades in-situ is a crucial task, for which remote monitoring via aerial survey from an Unmanned Aerial Vehicle (UAV) is commonplace. Turbine blades a... Read More about Semi-Supervised Surface Anomaly Detection of Composite Wind Turbine Blades From Drone Imagery.

Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss (2022)
Journal Article
Wang, Q., & Breckon, T. (2022). Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss. IEEE Transactions on Intelligent Transportation Systems, 23(9), 15233-15243. https://doi.org/10.1109/tits.2021.3138896

Automatic crowd behaviour analysis is an important task for intelligent transportation systems to enable effective flow control and dynamic route planning for varying road participants. Crowd counting is one of the keys to automatic crowd behaviour a... Read More about Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss.

DurLAR: A High-Fidelity 128-Channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-Modal Autonomous Driving Applications (2021)
Presentation / Conference Contribution
Li, L., Ismail, K. N., Shum, H. P., & Breckon, T. P. (2021, December). DurLAR: A High-Fidelity 128-Channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-Modal Autonomous Driving Applications. Presented at International Conference on 3D Vision, Surrey / Online

We present DurLAR, a high-fidelity 128-channel 3D LiDAR dataset with panoramic ambient (near infrared) and reflectivity imagery, as well as a sample benchmark task using depth estimation for autonomous driving applications. Our driving platform is eq... Read More about DurLAR: A High-Fidelity 128-Channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-Modal Autonomous Driving Applications.

Continuous Multi-modal Emotion Prediction in Video based on Recurrent Neural Network Variants with Attention (2021)
Presentation / Conference Contribution
Raju, J., Gaus, Y., & Breckon, T. (2021, December). Continuous Multi-modal Emotion Prediction in Video based on Recurrent Neural Network Variants with Attention. Presented at 20th IEEE International Conference on Machine Learning Applications

Contraband Materials Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery (2021)
Presentation / Conference Contribution
Wang, Q., & Breckon, T. (2021, December). Contraband Materials Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery. Presented at 20th IEEE International Conference on Machine Learning Applications

Operationalizing Convolutional Neural Network Architectures for Prohibited Object Detection in X-Ray Imagery (2021)
Presentation / Conference Contribution
Webb, T., Bhowmik, N., Gaus, Y., & Breckon, T. (2021, December). Operationalizing Convolutional Neural Network Architectures for Prohibited Object Detection in X-Ray Imagery. Presented at 20th IEEE International Conference on Machine Learning Applications

Re-ID-AR: Improved Person Re-identification in Video via Joint Weakly Supervised Action Recognition (2021)
Presentation / Conference Contribution
Alsehaim, A., & Breckon, T. (2021, November). Re-ID-AR: Improved Person Re-identification in Video via Joint Weakly Supervised Action Recognition. Presented at BMVC 2021, Online

We uniquely consider the task of joint person re-identification (Re-ID) and action recognition in video as a multi-task problem. In addition to the broader potential of joint Re-ID and action recognition within the context of automated multi-camera s... Read More about Re-ID-AR: Improved Person Re-identification in Video via Joint Weakly Supervised Action Recognition.