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Outputs (522)

NeFT-Net: N-window Extended Frequency Transformer for Rhythmic Motion Prediction (2025)
Journal Article
Ademola, A., Sinclair, D., Koniaris, B., Hannah, S., & Mitchell, K. (in press). NeFT-Net: N-window Extended Frequency Transformer for Rhythmic Motion Prediction. Computers and Graphics,

Advancements in prediction of human motion sequences are critical for enabling online virtual reality (VR) users to dance and move in ways that accurately mirror real-world actions, delivering a more immersive and connected experience. However, laten... Read More about NeFT-Net: N-window Extended Frequency Transformer for Rhythmic Motion Prediction.

HoloJig: Interactive Spoken Prompt Specified Generative AI Environments (2025)
Journal Article
Casas, L., Hannah, S., & Mitchell, K. (online). HoloJig: Interactive Spoken Prompt Specified Generative AI Environments. IEEE Computer Graphics and Applications, https://doi.org/10.1109/mcg.2025.3553780

HoloJig offers an interactive, speech-to-VR, virtual reality experience that generates diverse environments in real-time based on live spoken descriptions. Unlike traditional VR systems that rely on pre-built assets, HoloJig dynamically creates perso... Read More about HoloJig: Interactive Spoken Prompt Specified Generative AI Environments.

Machine learning for animatronic development and optimization (2025)
Patent
Mitchell, K., Castellon, J., Bacher, M., McCrory, M., Stolarz, J., & Ayala, A. (2025). Machine learning for animatronic development and optimization. US12236168B2

Techniques for animatronic design are provided. A plurality of simulated meshes is generated using a physics simulation model, where the plurality of simulated meshes corresponds to a plurality of actuator configurations for an animatronic mechanical... Read More about Machine learning for animatronic development and optimization.

Audio Occlusion Experiment Data (2025)
Data
McSeveney, S., Tamariz, M., McGregor, I., Koniaris, B., & Mitchell, K. (2025). Audio Occlusion Experiment Data. [Data]

This dataset comprises anonymous user study participant responses of audio occlusion to investigate presence response of body occlusions in the presence of sound sources in the direct path between the person and the audio driver speaker.

DeFT-Net: Dual-Window Extended Frequency Transformer for Rhythmic Motion Prediction (2024)
Presentation / Conference Contribution
Ademola, A., Sinclair, D., Koniaris, B., Hannah, S., & Mitchell, K. (2024, September). DeFT-Net: Dual-Window Extended Frequency Transformer for Rhythmic Motion Prediction. Presented at EG UK Computer Graphics & Visual Computing (2024), London, UK

Enabling online virtual reality (VR) users to dance and move in a way that mirrors the real-world necessitates improvements in the accuracy of predicting human motion sequences paving way for an immersive and connected experience. However, the drawba... Read More about DeFT-Net: Dual-Window Extended Frequency Transformer for Rhythmic Motion Prediction.

Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization (2024)
Journal Article
Zeng, L., Liu, Q., Shen, S., & Liu, X. (2024). Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization. Tsinghua Science and Technology, 29(3), 806 - 817. https://doi.org/10.26599/TST.2023.9010058

Edge computing nodes undertake more and more tasks as business density grows. How to efficiently allocate large-scale and dynamic workloads to edge computing resources has become a critical challenge. An edge task scheduling approach based on an impr... Read More about Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization.

DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences (2024)
Presentation / Conference Contribution
Koniaris, B., Sinclair, D., & Mitchell, K. (2024, March). DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences. Presented at IEEE VR Workshop on Open Access Tools and Libraries for Virtual Reality, Orlando, FL

DanceMark is an open telemetry framework designed for latency-sensitive real-time networked immersive experiences, focusing on online dancing in virtual reality within the DanceGraph platform. The goal is to minimize end-to-end latency and enhance us... Read More about DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences.

Method and system for visually seamless grafting of volumetric data (2024)
Patent
Mitchell, K. J. (2024). Method and system for visually seamless grafting of volumetric data

Visually seamless grafting of volumetric data. In some implementations, a method includes obtaining volumetric data that represents a first volume including one or more three-dimensional objects. Planar slices of the first volume are determined and f... Read More about Method and system for visually seamless grafting of volumetric data.

Expressive Talking Avatars (2024)
Journal Article
Pan, Y., Tan, S., Cheng, S., Lin, Q., Zeng, Z., & Mitchell, K. (2024). Expressive Talking Avatars. IEEE Transactions on Visualization and Computer Graphics, 30(5), 2538-2548. https://doi.org/10.1109/TVCG.2024.3372047

Stylized avatars are common virtual representations used in VR to support interaction and communication between remote collaborators. However, explicit expressions are notoriously difficult to create, mainly because most current methods rely on geome... Read More about Expressive Talking Avatars.

PFL-LDG: Privacy-preserving Federated Learning via Lightweight Device Grouping (2023)
Presentation / Conference Contribution
Wang, Z., Liu, Q., & Liu, X. (2023, August). PFL-LDG: Privacy-preserving Federated Learning via Lightweight Device Grouping. Presented at The 9th IEEE International Conference on Privacy Computing and Data Security (PCDS 2023) as Part of the IEEE Smart World Congress 2023, Portsmouth, UK

The rapid growth of private data from distributed edge networks, driven by the proliferation of IoT sensors, wearable devices, and smartphones, offers significant opportunities for AI applications. However, traditional distributed machine learning me... Read More about PFL-LDG: Privacy-preserving Federated Learning via Lightweight Device Grouping.

Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP (2023)
Presentation / Conference Contribution
Datta, S., Ganguly, D., Mothe, J., & Ullah, M. Z. (2023, April). Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP. Presented at 45th European Conference on Information Retrieval (ECIR), Dublin, Ireland

In information retrieval, query performance prediction aims to predict whether a search engine is likely to succeed in retrieving potentially relevant documents to a user's query. This problem is usually cast into a regression problem where a machine... Read More about Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP.

DanceGraph: A Complementary Architecture for Synchronous Dancing Online (2023)
Presentation / Conference Contribution
Sinclair, D., Ademola, A. V., Koniaris, B., & Mitchell, K. (2023, May). DanceGraph: A Complementary Architecture for Synchronous Dancing Online. Presented at 36th International Computer Animation & Social Agents (CASA) 2023, Limassol, Cyprus

DanceGraph is an architecture for synchronized online dancing overcoming the latency of net-worked body pose sharing. We break down this challenge by developing a real-time bandwidth-efficient architecture to minimize lag and reduce the timeframe of... Read More about DanceGraph: A Complementary Architecture for Synchronous Dancing Online.

Responsible Design & Evaluation of a Conversational Agent for a National Careers Service (2023)
Presentation / Conference Contribution
Wilson, M., Cruickshank, P., Gkatzia, D., & Robertson, P. (2023, September). Responsible Design & Evaluation of a Conversational Agent for a National Careers Service. Presented at Symposium on Future Directions in Information Access (FDIA) 2023, Vienna, Austria

This PhD project applies a research-through-design approach to the development of a conversational agent for a national career service for young people. This includes addressing practical, interactional and ethical aspects of the system. For each asp... Read More about Responsible Design & Evaluation of a Conversational Agent for a National Careers Service.

Real-time Facial Animation for 3D Stylized Character with Emotion Dynamics (2023)
Presentation / Conference Contribution
Pan, Y., Zhang, R., Wang, J., Ding, Y., & Mitchell, K. (2023, October). Real-time Facial Animation for 3D Stylized Character with Emotion Dynamics. Presented at 31st ACM International Conference on Multimedia, Ottawa, Canada

Our aim is to improve animation production techniques' efficiency and effectiveness. We present two real-time solutions which drive character expressions in a geometrically consistent and perceptually valid way. Our first solution combines keyframe a... Read More about Real-time Facial Animation for 3D Stylized Character with Emotion Dynamics.

Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges (2023)
Journal Article
Liu, Q., Yang, Z., Ji, R., Zhang, Y., Bilal, M., Liu, X., Vimal, S., & Xu, X. (2023). Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges. IEEE Systems, Man, and Cybernetics Magazine, 9(4), 4-12. https://doi.org/10.1109/msmc.2022.3216943

Radars are widely used to obtain echo information for effective prediction, such as precipitation nowcasting. In this article, recent relevant scientific investigation and practical efforts using deep learning (DL) models for weather radar data analy... Read More about Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges.

Towards Improving Accessibility of Web Auditing with Google Lighthouse (2023)
Presentation / Conference Contribution
McGill, T., Bamgboye, O., Liu, X., & Kalutharage, C. S. (2023, June). Towards Improving Accessibility of Web Auditing with Google Lighthouse. Presented at The 47th IEEE Annual Conference on Computers, Software, and Applications (COMPSAC), Turin, Italy

Google Lighthouse is a tool made by Google for auditing web pages performance, accessibility, SEO, and best practices with the intention of improving the quality of the websites. This allows software developers to understand areas of improvement with... Read More about Towards Improving Accessibility of Web Auditing with Google Lighthouse.