Skip to main content

Research Repository

Advanced Search

All Outputs (116)

Towards collaborative optimisation in a shared-logistics environment for pickup and delivery operations (2017)
Conference Proceeding
Curtois, T., Laesanklang, W., Landa-Silva, D., Mesgarpour, M., & Qu, Y. (2017). Towards collaborative optimisation in a shared-logistics environment for pickup and delivery operations. In Proceedings of the 6th International Conference on Operations Research and Enterprise Systems ICORES - Volume 1 (477-482)

This paper gives an overview of research work in progress within the COSLE (Collaborative Optimisation in a Shared Logistics Environment) project between the University of Nottingham and Microlise Ltd. This is an R&D project that seeks to develop opt... Read More about Towards collaborative optimisation in a shared-logistics environment for pickup and delivery operations.

Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem (2017)
Conference Proceeding
Algethami, H., Landa-Silva, D., & Martinez-Gavara, A. (2017). Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem. In Proceedings of the 6th International Conference on Operations Research and Enterprise Systems ICORES - Volume 1 (416-423)

The Workforce Scheduling and Routing Problem (WSRP) is a combinatorial optimisation problem that involves scheduling and routing of workforce. Tackling this type of problem often requires handling a considerable number of requirements, including cust... Read More about Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem.

Combining residual networks with LSTMs for lipreading (2017)
Conference Proceeding
Stafylakis, T., & Tzimiropoulos, G. (in press). Combining residual networks with LSTMs for lipreading. In Proc. Interspeech 2017 (3652-3656). https://doi.org/10.21437/Interspeech.2017-85

We propose an end-to-end deep learning architecture for word-level visual speech recognition. The system is a combination of spatiotemporal convolutional, residual and bidirectional Long Short-Term Memory networks. We train and evaluate it on the Lip... Read More about Combining residual networks with LSTMs for lipreading.

Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression (2017)
Conference Proceeding
Jackson, A. S., Bulat, A., Argyriou, V., & Tzimiropoulos, G. (2017). Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression. In Proceedings - 2017 IEEE International Conference on Computer Vision (1031-1039). https://doi.org/10.1109/ICCV.2017.117

3D face reconstruction is a fundamental Computer Vision problem of extraordinary difficulty. Current systems often assume the availability of multiple facial images (sometimes from the same subject) as input, and must address a number of methodologic... Read More about Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression.

Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources (2017)
Conference Proceeding
Bulat, A., & Tzimiropoulos, G. (2017). Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources. In Proceedings - 2017 IEEE International Conference on Computer Vision (ICCV 2017) (3726 - 3734). https://doi.org/10.1109/ICCV.2017.400

Our goal is to design architectures that retain the groundbreaking performance of CNNs for landmark localization and at the same time are lightweight, compact and suitable for applications with limited computational resources. To this end, we make th... Read More about Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources.

Social music machine: crowdsourcing for composition & creativity (2017)
Conference Proceeding
Chamberlain, A., De Roure, D., & Willcox, P. (2017). Social music machine: crowdsourcing for composition & creativity.

This poster describes a compositional technique that used crowd-sourced midi clips in order to develop a piece of music, which was later performed. This work in progress highlighted some of the issues facing the designers of systems that enable the ‘... Read More about Social music machine: crowdsourcing for composition & creativity.

The art and ‘science’ of opera: composing, staging & designing new forms of interactive theatrical performance (2017)
Conference Proceeding
Chamberlain, A., Kallionpää, M., & Benford, S. (2017). The art and ‘science’ of opera: composing, staging & designing new forms of interactive theatrical performance.

New technologies, such as Virtual Reality (VR), Robotics and Artificial Intelligence (AI) are steadily having an impact upon the world of opera. The evolving use of performance-based software such as Ableton Live and Max/MSP has created new and excit... Read More about The art and ‘science’ of opera: composing, staging & designing new forms of interactive theatrical performance.

An agent on my shoulder: AI, privacy and the application of human-like computing technologies to music creation (2017)
Conference Proceeding
Chamberlain, A., Malizia, A., & De Roure, D. (2017). An agent on my shoulder: AI, privacy and the application of human-like computing technologies to music creation.

Human-Like Computing technologies are intelligent systems that interact with people in human-like way. By bringing together the disciplines of Artificial Intelligence, Ethnography and Interaction Design, and applying them in a real world context we... Read More about An agent on my shoulder: AI, privacy and the application of human-like computing technologies to music creation.

Hearing the humanities: sonifying Steele’s Shakespeare (2017)
Conference Proceeding
Emsley, I., Chamberlain, A., & De Roure, D. (2017). Hearing the humanities: sonifying Steele’s Shakespeare.

We present initial work that explores the use of sonification to represent Joshua Steele’s symbolic notation. This provides a manner of overhearing a previous performance and testing the method’s reproducibility and uncertainties within it.

Abstract modelling: towards a typed declarative language for the conceptual modelling phase (2017)
Conference Proceeding
Legatiuk, D., & Nilsson, H. (2017). Abstract modelling: towards a typed declarative language for the conceptual modelling phase.

Modelling languages have become an indispensable aid to practising engineers. They offer modelling at a high level of abstraction backed by features such as automatic simulation and even derivation of production code. However, partly because of the o... Read More about Abstract modelling: towards a typed declarative language for the conceptual modelling phase.

Bread stories: understanding the drivers of bread consumption for digital food customisation (2017)
Conference Proceeding
Pantidi, N., Selinas, P., Flintham, M., Baurley, S., & Rodden, T. (2017). Bread stories: understanding the drivers of bread consumption for digital food customisation.

Consumer demand for food that satisfies specific needs rather than generic mass produced food is growing. In response, the food industry is actively investigating techniques for efficient and comprehensive food customisation. Digital approaches to fo... Read More about Bread stories: understanding the drivers of bread consumption for digital food customisation.

Extended Kalman filter-based learning of interval type-2 intuitionistic fuzzy logic system (2017)
Conference Proceeding
Eyoh, I., John, R., & De Maere, G. (2017). Extended Kalman filter-based learning of interval type-2 intuitionistic fuzzy logic system. In 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (728-733). https://doi.org/10.1109/SMC.2017.8122694

Fuzzy logic systems have been extensively applied for solving many real world application problems because they are found to be universal approximators and many methods, particularly, gradient descent (GD) methods have been widely adopted for the opt... Read More about Extended Kalman filter-based learning of interval type-2 intuitionistic fuzzy logic system.

The NoXi database: multimodal recordings of mediated novice-expert interactions (2017)
Conference Proceeding
Cafaro, A., Wagner, J., Baur, T., Dermouche, S., Torres, M. T., Pelachaud, C., …Valstar, M. F. (2017). The NoXi database: multimodal recordings of mediated novice-expert interactions.

We present a novel multi-lingual database of natural dyadic novice-expert interactions, named NoXi, featuring screen-mediated dyadic human interactions in the context of information exchange and retrieval. NoXi is designed to provide spontaneous inte... Read More about The NoXi database: multimodal recordings of mediated novice-expert interactions.

THCluster: herb supplements categorization for precision traditional Chinese medicine (2017)
Conference Proceeding
Ruan, C., Wang, Y., Zhang, Y., Ma, J., Chen, H., Aickelin, U., …Zhang, T. (2017). THCluster: herb supplements categorization for precision traditional Chinese medicine.

There has been a continuing demand for traditional and complementary medicine worldwide. A fundamental and important topic in Traditional Chinese Medicine (TCM) is to optimize the prescription and to detect herb regularities from TCM data. In this pa... Read More about THCluster: herb supplements categorization for precision traditional Chinese medicine.

Visual landmark sequence-based indoor localization (2017)
Conference Proceeding
Li, Q., Zhu, J., Liu, T., Garibaldi, J., Li, Q., & Qiu, G. (2017). Visual landmark sequence-based indoor localization. In Proceedings of the 1st Workshop on Artificial Intelligence and Deep Learning for Geographic Knowledge Discovery - GeoAI '17 (14-23). https://doi.org/10.1145/3149808.3149812

This paper presents a method that uses common objects as landmarks for smartphone-based indoor localization and navigation. First, a topological map marking relative positions of common objects such as doors, stairs and toilets is generated from floo... Read More about Visual landmark sequence-based indoor localization.

Cumulative attributes for pain intensity estimation (2017)
Conference Proceeding
Joy, E., & Valstar, M. (2017). Cumulative attributes for pain intensity estimation. In ICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction (146-153). https://doi.org/10.1145/3136755.3136789

Pain estimation from face video is a hard problem in automatic behaviour understanding. One major obstacle is the difficulty of collecting sufficient amounts of data, with balanced amounts of data for all pain intensity levels. To overcome this, we p... Read More about Cumulative attributes for pain intensity estimation.

Determining firing strengths through a novel similarity measure to enhance uncertainty handling in non-singleton fuzzy logic systems (2017)
Conference Proceeding
Pekaslan, D., Kabir, S., Wagner, C., & Garibaldi, J. M. (2017). Determining firing strengths through a novel similarity measure to enhance uncertainty handling in non-singleton fuzzy logic systems. In Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 0IJCCI (83-90). https://doi.org/10.5220/0006502000830090

Non-singleton Fuzzy Logic Systems have the potential to tackle uncertainty within the design of fuzzy systems. The inference process has a major role in determining results, being partly based on the interaction of input and antecedent fuzzy sets (in... Read More about Determining firing strengths through a novel similarity measure to enhance uncertainty handling in non-singleton fuzzy logic systems.

How Far are We from Solving the 2D & 3D Face Alignment Problem? (and a Dataset of 230,000 3D Facial Landmarks) (2017)
Conference Proceeding
Bulat, A., & Tzimiropoulos, G. (2017). How Far are We from Solving the 2D & 3D Face Alignment Problem? (and a Dataset of 230,000 3D Facial Landmarks). In 2017 IEEE International Conference on Computer Vision (ICCV 2017) (1021-1030). https://doi.org/10.1109/ICCV.2017.116

This paper investigates how far a very deep neural network is from attaining close to saturating performance on existing 2D and 3D face alignment datasets. To this end, we make the following 5 contributions: (a) we construct, for the first time, a ve... Read More about How Far are We from Solving the 2D & 3D Face Alignment Problem? (and a Dataset of 230,000 3D Facial Landmarks).

Synergy between face alignment and tracking via Discriminative Global Consensus Optimization (2017)
Conference Proceeding
Khan, M. H., McDonagh, J., & Tzimiropoulos, G. (2017). Synergy between face alignment and tracking via Discriminative Global Consensus Optimization.

An open question in facial landmark localization in video is whether one should perform tracking or tracking-by-detection (i.e. face alignment). Tracking produces fittings of high accuracy but is prone to drifting. Tracking-by-detection is drift-free... Read More about Synergy between face alignment and tracking via Discriminative Global Consensus Optimization.