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Dual encoding for abstractive text summarization (2018)
Journal Article
Yao, K., Zhang, L., Du, D., Luo, T., Tao, L., & Wu, Y. (2020). Dual encoding for abstractive text summarization. IEEE Transactions on Cybernetics, 50(3), 985-996. https://doi.org/10.1109/TCYB.2018.2876317

Recurrent Neural Network (RNN) based sequence-to-sequence attentional models have proven effective in abstractive text summarization. In this paper, we model abstractive text summarization using a dual encoding model. Different from the previous work... Read More about Dual encoding for abstractive text summarization.

Teaching machines to ask questions (2018)
Presentation / Conference
Yao, K., Zhang, L., Luo, T., Tao, L., & Wu, Y. (2018, July). Teaching machines to ask questions. Paper presented at International Joint Conferences on Artificial Intelligence Organization

We propose a novel neural network model that aims to generate diverse and human-like natural language questions. Our model not only directly captures the variability in possible questions by using a latent variable, but also generates certain types o... Read More about Teaching machines to ask questions.

Energy expenditure estimation using visual and inertial sensors (2017)
Journal Article
Craddock, I., Paiement, A., Hannuna, S., Camplani, M., Cooper, A., Damen, D., …Tao, L. (2018). Energy expenditure estimation using visual and inertial sensors. IET Computer Vision, 12(1), 36-47. https://doi.org/10.1049/iet-cvi.2017.0112

© The Institution of Engineering and Technology 2017. Deriving a person's energy expenditure accurately forms the foundation for tracking physical activity levels across many health and lifestyle monitoring tasks. In this study, the authors present a... Read More about Energy expenditure estimation using visual and inertial sensors.

Multiple human tracking in RGB-depth data: A survey (2017)
Journal Article
Camplani, M., Paiement, A., Mirmehdi, M., Damen, D., Hannuna, S., Burghardt, T., & Tao, L. (2017). Multiple human tracking in RGB-depth data: A survey. IET Computer Vision, 11(4), 265-285. https://doi.org/10.1049/iet-cvi.2016.0178

© The Institution of Engineering and Technology. Multiple human tracking (MHT) is a fundamental task in many computer vision applications. Appearance-based approaches, primarily formulated on RGB data, are constrained and affected by problems arising... Read More about Multiple human tracking in RGB-depth data: A survey.

DS-KCF: a real-time tracker for RGB-D data (2016)
Journal Article
Hannuna, S., Camplani, M., Hall, J., Mirmehdi, M., Damen, D., Burghardt, T., …Tao, L. (2019). DS-KCF: a real-time tracker for RGB-D data. Journal of Real-Time Image Processing, 16(5), 1439-1458. https://doi.org/10.1007/s11554-016-0654-3

© 2016 The Author(s) We propose an RGB-D single-object tracker, built upon the extremely fast RGB-only KCF tracker that is able to exploit depth information to handle scale changes, occlusions, and shape changes. Despite the computational demands of... Read More about DS-KCF: a real-time tracker for RGB-D data.

A comparative study of pose representation and dynamics modelling for online motion quality assessment (2016)
Journal Article
Tao, L., Paiement, A., Damen, D., Mirmehdi, M., Hannuna, S., Camplani, M., …Craddock, I. (2016). A comparative study of pose representation and dynamics modelling for online motion quality assessment. Computer Vision and Image Understanding, 148, 136-152. https://doi.org/10.1016/j.cviu.2015.11.016

© 2015 The Authors. Published by Elsevier Inc. Quantitative assessment of the quality of motion is increasingly in demand by clinicians in healthcare and rehabilitation monitoring of patients. We study and compare the performances of different pose r... Read More about A comparative study of pose representation and dynamics modelling for online motion quality assessment.

Robust deformable shape reconstruction from monocular video with manifold forests (2016)
Journal Article
Matuszewski, B. J., Tao, L., & Matuszewski, B. (2016). Robust deformable shape reconstruction from monocular video with manifold forests. Machine Vision and Applications, 27(6), 801-819. https://doi.org/10.1007/s00138-016-0769-3

© 2016, The Author(s). Existing approaches to recover structure of 3D deformable objects and camera motion parameters from an uncalibrated images assume the object’s shape could be modelled well by a linear subspace. These methods have been proven ef... Read More about Robust deformable shape reconstruction from monocular video with manifold forests.

Bridging eHealth and the Internet of Things: The SPHERE Project (2015)
Journal Article
Zhu, N., Diethe, T., Camplani, M., Tao, L., Burrows, A., Twomey, N., …Craddock, I. (2015). Bridging eHealth and the Internet of Things: The SPHERE Project. IEEE Intelligent Systems, 30(4), 39-46

There is a widely-accepted need to revise current forms of healthcare provision. Of particular interest are sensing systems in the home, which have been central to a number of studies in this area. This paper presents an overview of this rapidly grow... Read More about Bridging eHealth and the Internet of Things: The SPHERE Project.

3D convolutional neural network for home monitoring using low resolution thermal-sensor array
Presentation / Conference
Tao, L., Volonakis, T., Tan, B., Zhang, Z., Jing, Y., & Smith, M. 3D convolutional neural network for home monitoring using low resolution thermal-sensor array

The recognition of daily actions, such as walking, sitting or standing, in the home is informative for assisted living, smart homes and general health care. A variety of actions in complex scenes can be recognised using visual information. However ca... Read More about 3D convolutional neural network for home monitoring using low resolution thermal-sensor array.