Outputs (522)

Hardware Design for Autonomous Robot Evolution (2020)
Presentation / Conference Contribution
Hale, M. F., Angus, M., Buchanan, E., Li, W., Woolley, R., Le Goff, L. K., De Carlo, M., Timmis, J., Winfield, A. F., Hart, E., Eiben, A. E., & Tyrrell, A. M. (2020, December). Hardware Design for Autonomous Robot Evolution. Presented at International Conference on Evolvable Hardware, Canberra Australia

The long term goal of the Autonomous Robot Evolution (ARE) project is to create populations of physical robots, in which both the controllers and body plans are evolved. The transition for evolutionary designs from purely simulation environments into... Read More about Hardware Design for Autonomous Robot Evolution.

Evolution of Diverse, Manufacturable Robot Body Plans (2020)
Presentation / Conference Contribution
Buchanan, E., Le Goff, L., Hart, E., Eiben, A. E., De Carlo, M., Li, W., Hale, M. F., Angus, M., Woolley, R., Winfield, A. F., Timmis, J., & Tyrrell, A. M. (2020, December). Evolution of Diverse, Manufacturable Robot Body Plans. Presented at International Conference on Evolvable Systems (ICES), Canberra, Australia

Advances in rapid prototyping have opened up new avenues of research within Evolutionary Robotics in which not only controllers but also the body plans (morphologies) of robots can evolve in real-time and real-space. However, this also introduces new... Read More about Evolution of Diverse, Manufacturable Robot Body Plans.

Commonsense-enhanced Natural Language Generation for Human-Robot Interaction (2020)
Presentation / Conference Contribution
Gkatzia, D. (2020, December). Commonsense-enhanced Natural Language Generation for Human-Robot Interaction. Presented at 2nd Workshop on Natural Language Generation for Human-Robot Interaction (HRI 2020), Online

Commonsense is vital for human communication, as it allows us to make inferences without explicitly mentioning the context. Equipping robots with commonsense knowledge would lead to better communication between humans and robots and will allow robots... Read More about Commonsense-enhanced Natural Language Generation for Human-Robot Interaction.

Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation (2020)
Presentation / Conference Contribution
Hoffmann, B., Urquhart, N., Chalmers, K., & Guckert, M. (2020, February). Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation. Presented at Modelling 2020, Vienna

Multi-agent systems may be considered appropriate tools for simulating complex systems such as those based around traffic and transportation networks. Modelling traffic participants as agents can reveal relevant patterns of traffic flow. Upsurging tr... Read More about Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation.

A Fast Classification Approach to Upper-Limb Posture Recognition (2020)
Presentation / Conference Contribution
Wu, X., Jiang, Y., Liu, Q., Wu, H., & Liu, X. (2020, November). A Fast Classification Approach to Upper-Limb Posture Recognition. Presented at IEEE International Conferences on Cyber, Physical and Social Computing (CPSCom2020), Rhodes, Greece

Drawing Algorithms For Linear Diagrams (Supplementary) (2020)
Data
Chapman, P., & Sim, K. (2021). Drawing Algorithms For Linear Diagrams (Supplementary). [Data]. https://doi.org/10.17869/enu.2021.2748170

This folder contains the material to go with the article:

Peter Chapman, Kevin Sim, Huanghao Chen (2021) Drawing Algorithms for Linear Diagrams.

The code, the benchmark set of diagrams, the dataset of algorithms applied to the benchmark set, an... Read More about Drawing Algorithms For Linear Diagrams (Supplementary).

FaceMagic: Real-time Facial Detail Effects on Mobile (2020)
Presentation / Conference Contribution
Casas, L., Li, Y., & Mitchell, K. (2020, December). FaceMagic: Real-time Facial Detail Effects on Mobile. Presented at SA '20: SIGGRAPH Asia 2020, Online [Republic of Korea]

We present a novel real-time face detail reconstruction method capable of recovering high quality geometry on consumer mobile devices. Our system firstly uses a morphable model and semantic segmentation of facial parts to achieve robust self-calibrat... Read More about FaceMagic: Real-time Facial Detail Effects on Mobile.

Improving VIP viewer Gaze Estimation and Engagement Using Adaptive Dynamic Anamorphosis (2020)
Journal Article
Pan, Y., & Mitchell, K. (2021). Improving VIP viewer Gaze Estimation and Engagement Using Adaptive Dynamic Anamorphosis. International Journal of Human-Computer Studies, 147, Article 102563. https://doi.org/10.1016/j.ijhcs.2020.102563

Anamorphosis for 2D displays can provide viewer centric perspective viewing, enabling 3D appearance, eye contact and engagement, by adapting dynamically in real time to a single moving viewer’s viewpoint, but at the cost of distorted viewing for othe... Read More about Improving VIP viewer Gaze Estimation and Engagement Using Adaptive Dynamic Anamorphosis.

Animation Streaming for Media Interaction (2020)
Patent
Mitchell, K. (2020). Animation Streaming for Media Interaction. US20200334886

Embodiments provide for animation streaming for media interaction by receiving, at a generator, inputs from a target device presenting of a virtual environment; updating, based on the user inputs, a model of the virtual environment; determining netwo... Read More about Animation Streaming for Media Interaction.

Active Learning for Interactive Audio-Animatronic Performance Design (2020)
Journal Article
Castellon, J., Bächer, M., McCrory, M., Ayala, A., Stolarz, J., & Mitchell, K. (2020). Active Learning for Interactive Audio-Animatronic Performance Design. The Journal of Computer Graphics Techniques, 9(3), 1-19

We present a practical neural computational approach for interactive design of Audio-Animatronic® facial performances. An offline quasi-static reference simulation, driven by a coupled mechanical assembly, accurately predicts hyperelastic skin deform... Read More about Active Learning for Interactive Audio-Animatronic Performance Design.

Visual Encodings for Networks with Multiple Edge Types (2020)
Presentation / Conference Contribution
Vogogias, T., Archambault, D. W., Bach, B., & Kennedy, J. (2020, October). Visual Encodings for Networks with Multiple Edge Types. Presented at International Conference on Advanced Visual Interfaces, Napkes, Italy

This paper reports on a formal user study on visual encodings of networks with multiple edge types in adjacency matrices. Our tasks and conditions were inspired by real problems in computational biology. We focus on encodings in adjacency matrices, s... Read More about Visual Encodings for Networks with Multiple Edge Types.

A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles (2020)
Journal Article
Liu, Q., Kamoto, K. M., Liu, X., Zhang, Y., Yang, Z., Khosravi, M. R., Xu, Y., & Qi, L. (2021). A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles. IEEE Sensors Journal, 21(14), 15895-15903. https://doi.org/10.1109/jsen.2020.3027684

Intelligent transportation systems (ITSs) have become popular in recent years as an essential requirement for safer and more efficient transportation systems. Internet of Electric vehicles (IoEV) as well as their hybrid forms provide an ideal means o... Read More about A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles.

Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples (2020)
Presentation / Conference Contribution
Babaagba, K., Tan, Z., & Hart, E. (2020, July). Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples. Presented at The 2020 IEEE Congress on Evolutionary Computation (IEEE CEC 2020), Glasgow, UK

Detecting metamorphic malware provides a challenge to machine-learning models as trained models might not generalise to future mutant variants of the malware. To address this, we explore whether machine-learning models can be improved by augmenting t... Read More about Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples.

A secure edge monitoring approach to unsupervised energy disaggregation using mean shift algorithm in residential buildings (2020)
Journal Article
Liu, Q., Nakoty, F. M., Wu, X., Anaadumba, R., Liu, X., Zhang, Y., & Qi, L. (2020). A secure edge monitoring approach to unsupervised energy disaggregation using mean shift algorithm in residential buildings. Computer Communications, 162, 187-195. https://doi.org/10.1016/j.comcom.2020.08.024

Compared to Intrusive Load Monitoring which uses smart power meters at each level to be monitored, Non-Intrusive Load Monitoring (NILM) is an ingenious way that relies on signal readings at a single point to deduce the share of the devices that have... Read More about A secure edge monitoring approach to unsupervised energy disaggregation using mean shift algorithm in residential buildings.

Props Alive: A Framework for Augmented Reality Stop Motion Animation (2020)
Presentation / Conference Contribution
Casas, L., Kosek, M., & Mitchell, K. (2017, March). Props Alive: A Framework for Augmented Reality Stop Motion Animation. Presented at 2017 IEEE 10th Workshop on Software Engineering and Architectures for Realtime Interactive Systems (SEARIS), Los Angeles, CA, USA

Stop motion animation evolved in the early days of cinema with the aim to create an illusion of movement with static puppets posed manually each frame. Current stop motion movies introduced 3D printing processes in order to acquire animations more ac... Read More about Props Alive: A Framework for Augmented Reality Stop Motion Animation.

A mechanism to promote social behaviour in household load balancing (2020)
Presentation / Conference Contribution
Brooks, N. A., Powers, S. T., & Borg, J. M. (2020, July). A mechanism to promote social behaviour in household load balancing. Presented at The 2020 Conference on Artificial Life, Montreal, Canada

Reducing the peak energy consumption of households is essential for the effective use of renewable energy sources, in order to ensure that as much household demand as possible can be met by renewable sources. This entails spreading out the use of hig... Read More about A mechanism to promote social behaviour in household load balancing.

Monthly Precipitation Forecasts Using Wavelet Neural Networks Models in a Semiarid Environment (2020)
Journal Article
Estévez, J., Bellido-Jiménez, J. A., Liu, X., & García-Marín, A. P. (2020). Monthly Precipitation Forecasts Using Wavelet Neural Networks Models in a Semiarid Environment. Water, 12(7), Article 1909. https://doi.org/10.3390/w12071909

Accurate forecast of hydrological data such as precipitation is critical in order to provide useful information for water resources management, playing a key role in different sectors. Traditional forecasting methods present many limitations due to t... Read More about Monthly Precipitation Forecasts Using Wavelet Neural Networks Models in a Semiarid Environment.

A Survey of Error Analysis and Calibration Methods for MEMS Triaxial Accelerometers (2020)
Journal Article
Xiao, B., Jiang, Y., Liu, Q., Liu, X., & Sun, M. (2020). A Survey of Error Analysis and Calibration Methods for MEMS Triaxial Accelerometers. Computers, Materials & Continua, 64(1), 389-399. https://doi.org/10.32604/cmc.2020.06092

MEMS accelerometers are widely used in various fields due to their small size and low cost, and have good application prospects. However, the low accuracy limits its range of applications. To ensure data accuracy and safety we need to calibrate MEMS... Read More about A Survey of Error Analysis and Calibration Methods for MEMS Triaxial Accelerometers.

Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites (2020)
Presentation / Conference Contribution
Babaagba, K. O., Tan, Z., & Hart, E. (2020, April). Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites. Presented at EvoStar 2020, Seville, Spain

In the field of metamorphic malware detection, training a detection model with malware samples that reflect potential mutants of the malware is crucial in developing a model resistant to future attacks. In this paper, we use a Multi-dimensional Archi... Read More about Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites.

Group-Based Expert Walkthroughs: How Immersive Technologies Can Facilitate the Collaborative Authoring of Character Animation (2020)
Presentation / Conference Contribution
Pan, Y., & Mitchell, K. (2020, March). Group-Based Expert Walkthroughs: How Immersive Technologies Can Facilitate the Collaborative Authoring of Character Animation. Presented at 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), Atlanta, GA, USA

Immersive technologies have increasingly attracted the attention of the computer animation community in search of more intuitive and effective alternatives to the current sophisticated 2D interfaces. The higher affordances offered by 3D interaction,... Read More about Group-Based Expert Walkthroughs: How Immersive Technologies Can Facilitate the Collaborative Authoring of Character Animation.