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Prof Kenny Mitchell's Outputs (4)

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.

NeFT-Net: N-window extended frequency transformer for rhythmic motion prediction (2025)
Journal Article
Ademola, A., Sinclair, D., Koniaris, B., Hannah, S., & Mitchell, K. (2025). NeFT-Net: N-window extended frequency transformer for rhythmic motion prediction. Computers and Graphics, 129, Article 104244. https://doi.org/10.1016/j.cag.2025.104244

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. (2025). HoloJig: Interactive Spoken Prompt Specified Generative AI Environments. IEEE Computer Graphics and Applications, 45(2), 69-77. 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.

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.