Portrait of Dr Konstantinos Sirlantzis

Dr Konstantinos Sirlantzis

Senior Lecturer in Intelligent Systems


Pattern Recognition; Multiple Classifier Systems; Artificial Intelligence techniques; Neural Networks, Genetic Algorithms, and other Biologically Inspired Computing Paradigms; Image Processing; Multimodal Biometric Models; Handwriting Recognition; Numerical Stochastic Optimisation Algorithms; Non-linear Dynamics and Chaos Theory; Markov Chain Monte Carlo (MCMC) methods for Sensor Data Fusion.

Research interests


Showing 50 of 112 total publications in the Kent Academic Repository. View all publications.


  • Hu, Y., Sirlantzis, K. and Howells, G. (2016). A novel iris weight map method for less constrained iris recognition based on bit stability and discriminability. Image and Vision Computing [Online] 58:168-180. Available at: http://dx.doi.org/10.1016/j.imavis.2016.05.003.
    In this paper, we propose and investigate a novel iris weight map method for iris matching stage to improve less constrained iris recognition. The proposed iris weight map considers both intra-class bit stability and inter-class bit discriminability of iris codes. We model the intra-class bit stability in a stability map to improve the intra-class matching. The stability map assigns more weight to the bits that have values more consistent with their noiseless and stable estimates obtained using a low rank approximation from a set of noisy training images. Also, we express the inter-class bit discriminability in a discriminability map to enhance the inter-class separation. We calculate the discriminability map using a 1-to-N strategy, emphasizing the bits with more discriminative power in iris codes. The final iris weight map is the combination of the stability map and the discriminability map. We conduct experimental analysis on four publicly available datasets captured in varying less constrained conditions. The experimental results demonstrate that the proposed iris weight map achieves generally improved identification and verification performance compared to state-of-the-art methods.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2016). Signal-Level Information Fusion for Less Constrained Iris Recognition using Sparse-Error Low Rank Matrix Factorization. IEEE Transactions on Information Forensics and Security [Online]:1549-1564. Available at: http://dx.doi.org/10.1109/TIFS.2016.2541612.
    Iris recognition systems working in less constrained environments with the subject at-a-distance and on-the-move suffer from the noise and degradations in the iris captures. These noise and degradations significantly deteriorate iris recognition performance. In this paper, we propose a novel signal-level information fusion method to mitigate the influence of noise and degradations for less constrained iris recognition systems. The proposed method is based on low rank approximation (LRA). Given multiple noisy captures of the same eye, we assume that: 1) the potential noiseless images lie in a low rank subspace and 2) the noise is spatially sparse. Based on these assumptions, we seek an LRA of noisy captures to separate the noiseless images and noise for information fusion. Specifically, we propose a sparse-error low rank matrix factorization model to perform LRA, decomposing the noisy captures into a low rank component and a sparse error component. The low rank component estimates the potential noiseless images, while the error component models the noise. Then, the low rank and error components are utilized to perform signal-level fusion separately, producing two individually fused images. Finally, we combine the two fused images at the code level to produce one iris code as the final fusion result. Experiments on benchmark data sets demonstrate that the proposed signal-level fusion method is able to achieve a generally improved iris recognition performance in less constrained environment, in comparison with the existing iris recognition algorithms, especially for the iris captures with heavy noise and low quality.
  • Hu, Y. et al. (2016). An online background subtraction algorithm deployed on a NAO humanoid robot based monitoring system. Robotics and Autonomous Systems [Online] 85:37-47. Available at: http://dx.doi.org/10.1016/j.robot.2016.08.013.
    In this paper, we design a fast background subtraction algorithm and deploy this algorithm on a monitoring system
    based on NAO humanoid robot. The proposed algorithm detects a contiguous foreground via a contiguously weighted
    linear regression (CWLR) model. It consists of a background model and a foreground model. The background model
    is a regression based low rank model. It seeks a low rank background subspace and represents the background as the
    linear combination of the basis spanning the subspace. The foreground model promotes the contiguity in the foreground
    detection. It encourages the foreground to be detected as whole regions rather than separated pixels. We formulate
    the background and foreground model into a contiguously weighted linear regression problem. This problem can be
    solved efficiently via an alternating optimization approach which includes continuous and discrete variables. Given an
    image sequence, we use the first few frames to incrementally initialize the background subspace, and we determine
    the background and foreground in the following frames in an online scheme using the proposed CWLR model, with
    the background subspace continuously updated using the detected background information. The proposed algorithm is
    implemented by Python on a NAO humanoid robot based monitoring system. This system consists of a control station
    and a Nao robot. The Nao robot acts as a mobile probe. It captures image sequence and sends it to the control station.
    The control station serves as a control terminal. It sends commands to control the behaviour of Nao robot, and it
    processes the image data sent by Nao. This system can be used for living environment monitoring and form the basis for
    many vision-based applications like fall detection and scene understanding. The experimental comparisons with most
    recent algorithms on both benchmark dataset and NAO captures demonstrate the high effectiveness of the proposed
  • Nasri, Y. et al. (2016). ROS-based Autonomous Navigation Wheelchair using Omnidirectional Sensor. International Journal of Computer Applications [Online] 133. Available at: http://dx.doi.org/10.5120/ijca2016907533.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2016). Optimal Generation of Iris Codes for Iris Recognition. IEEE Transactions on Information Forensics and Security [Online]. Available at: http://doi.org/10.1109/TIFS.2016.2606083.
    The calculation of binary iris codes from feature values (e.g. the result of Gabor transform) is a key step in iris recognition systems. Traditional binarization method based on the sign of feature values has achieved very promising performance. However, currently, little research focuses on a deeper insight into this binarization method to produce iris codes. In this paper, we illustrate the iris code calculation from the perspective of optimization. We demonstrate that the traditional iris code is the solution of an optimization problem which minimizes the distance between the feature values and iris codes. Furthermore, we show that more effective iris codes can be obtained by adding terms to the objective function of this optimization problem. We investigate two additional objective terms. The first objective term exploits the spatial relationships of the bits in different positions of an iris code. The second objective term mitigates the influence of less reliable bits in iris codes. The two objective terms can be applied to the optimization problem individually, or in a combined scheme. We conduct experiments on four benchmark datasets with varying image quality. The experimental results demonstrate that the iris code produced by solving the optimization problem with the two additional objective terms achieves a generally improved performance in comparison to the traditional iris code calculated by binarizing feature values based on their signs.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2015). Improving colour iris segmentation using a model selection technique. Pattern Recognition Letters [Online] 57:24-32. Available at: http://doi.org/10.1016/j.patrec.2014.12.012.
    In this paper, we propose a novel method to improve the reliability and accuracy of colour iris segmentation for captures both from static and mobile devices. Our method is a fusion strategy based on selection among the segmentation outcomes of different segmentation methods or models. First, we present and analyse an iris segmentation framework which uses three different models to show that improvements can be obtained by selection among the outcomes generated by the three models. Then, we introduce a model selection method which defines the optimal segmentation based on a ring-shaped region around the outer segmentation boundary identified by each model. We use the histogram of oriented gradients (HOG) as features extracted from the ring-shaped region, and train a SVM-based classifier which provides the selection decision. Experiments on colour iris datasets, captured by mobile devices and static camera, show that the proposed method achieves an improved performance compared to the individual iris segmentation models and existing algorithms.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2015). Iris liveness detection using regional features. Pattern Recognition Letters [Online]. Available at: https://doi.org/10.1016/j.patrec.2015.10.010.
    In this paper, we exploit regional features for iris liveness detection. Regional features are designed based on the relationship of the features in neighbouring regions. They essentially capture the feature distribution among neighbouring regions. We construct the regional features via two models: spatial pyramid and relational measure which seek the feature distributions in regions with varying size and shape respectively. The spatial pyramid model extracts features from coarse to fine grid regions, and, it models a local to global feature distribution. The local distribution captures the local feature variations while the global distribution includes the information that is more robust to translational transform. The relational measure is based on a feature-level convolution operation defined in this paper. By varying the shape of the convolution kernel, we are able to obtain the feature distribution in regions with different shapes. To combine the feature distribution information in regions with varying size and shape, we fuse the results based on the two models at the score level. Experimental results on benchmark datasets demonstrate that the proposed method achieves an improved performance compared to state-of-the-art features.
  • Radu, P. et al. (2013). A Colour Iris Recognition System Employing Multiple Classifier Techniques. ELCVIA Electronic Letters on Computer Vision and Image Analysis [Online] 12:54-65. Available at: http://elcvia.cvc.uab.es/article/view/520.
    The randomness of iris texture has allowed researchers to develop biometric systems with almost flawless accuracies. However, a common drawback of the majority of existing iris recognition systems is the constrained environment in which the user is enroled and recognized. The iris recognition systems typically require a high quality iris image captured under near infrared illumination. A desirable property of an iris recognition system is to be able to operate on colour images, whilst maintaining a high accuracy. In the present work we propose an iris recognition methodology which is designed to cope with noisy colour iris images. There are two main contributions of this paper: first, we adapt standard iris features proposed in literature for near infrared images by applying a feature selection method on features extracted from various colour channels; second, we introduce a Multiple Classifier System architecture to enhance the recognition accuracy of the biometric system. With a feature size of only 360 real valued components, the proposed iris recognition system performs with a high accuracy on UBIRISv1 dataset, in both identification and verfication scenarios.
  • Radu, P. et al. (2013). A review of information fusion techniques employed in iris recognition systems. International Journal of Advanced Intelligence Paradigms [Online] 4:211-240. Available at: http://dx.doi.org/10.1504/IJAIP.2012.052067.
    Iris recognition has shown to be one of the most reliable biometric authentication methods. The majority of iris recognition systems which have been developed require a constrained environment to enrol and recognise the user. If the user is not cooperative or the capture environment changes then the accuracy of the iris recognition system may decrease significantly. To minimise the effect of such limitations, possible solutions include the use of multiple channels of information such as using both eyes or extracting more iris feature types and subsequently employing an efficient fusion method. In this paper, we present a review of iris recognition systems using information from multiple sources that are fused in different ways or at different levels. A categorisation of the iris recognition systems incorporating multiple classifier systems is also presented. As a new desirable dimension of a biometric system, besides those proposed in the literature, the mobility of such a system is introduced in this work. The review charts the path towards greater flexibility and robustness of iris recognition systems through the use of information fusion techniques and points towards further developments in the future leading to mobile and ubiquitous deployment of such systems.
  • Radu, P. et al. (2011). Information Fusion for Unconstrained Iris Recognition. International Journal of Hybrid Information Technology 4:1-12.
    The majority of the iris recognition algorithms available in the literature were developed to operate on near infrared images. A desirable feature of iris recognition systems with reduced constraints such as potential operability on commonly available hardware is to work with images acquired under visible wavelength. Unlike in near infrared images, in colour iris images the pigment melanin present in the iris tissue causes the appearance of reflections, which are one of the major noise factors present in colour iris images. In this paper we present an iris recognition system which is able to cope with noisy colour iris images by employing score level fusion between different channels of the iris image. The robustness of the proposed approach is tested on three colour iris images datasets, ranging from images captured with professional cameras in both constrained environment and less cooperative scenario, and finally to iris images acquired with a mobile phone.
  • McConnon, G. et al. (2011). An Investigation of Quality Aspects of Noisy Colour Images for Iris Recognition. International Journal of Signal Processing, Image Processing and Pattern Recognition [Online] 4:165-178. Available at: http://www.sersc.org/journals/IJSIP/vol4_no3.php.
    The UBIRIS.v2 dataset is a set of noisy colour iris images designed to simulate visible wavelength iris acquisition at-a-distance and on-the-move. This paper presents an examination of some of the characteristics that can impact the performance of iris recognition in the UBIRIS.v2 dataset. This dataset consists of iris images in the visible wavelength and was designed to be noisy. The quality and characteristics of these images are surveyed by examining seven different channels of information extracted from them: red, green, blue, intensity, value, lightness, and luminance. We present new quality metrics to assess the image characteristics with regard to focus, entropy, reflections, pupil constriction and pupillary boundary contrast. The results clearly suggest the existence of different characteristics for these channels and could be exploited for use in the design and evaluation of iris recognition systems.

Book section

  • O'Brien, J. et al. (2017). Automated Cell Segmentation of Fission Yeast Phase Images - Segmenting Cells from Light Microscopy Images. in: Silveira, M. et al. eds. Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies. Scitepress, pp. 92-99. Available at: http://dx.doi.org/10.5220/0006149100920099.
    Robust image analysis is an important aspect of all cell biology studies. The geometrics of cells are critical for developing an understanding of biological processes. Time constraints placed on researchers lead to a narrower focus on what data are collected and recorded from an experiment, resulting in a loss of data. Currently, preprocessing of microscope images is followed by the utilisation and parameterisation of inbuilt functions of various softwares to obtain information. Using the fission yeast, Schizosaccharomyes pombe, we propose a novel, fully automated, segmentation software for cells with a significantly lower rate of segmentation errors than PombeX with the same dataset.
  • Spanogianopoulos, S. and Sirlantzis, K. (2016). Car-Like Mobile Robot Navigation: A Survey. in: Tsihrintzis, G., Virvou, M. and Jain, L. C. eds. Intelligent Computing Systems: Emerging Application Areas. Berlin Heidelberg: Springer-Verlag Berlin Heidelberg. Available at: http://dx.doi.org/10.1007/978-3-662-49179-9_14.
    Car-like mobile robot navigation has been an active and challenging field both in academic research an in industry over the last few decades, and it has opened the way to build and test (recently) autonomously driven robotic cars which can negotiate the complexity and uncertainties introduced by real urban and suburban environments. In this chapter, we review the basic principles and discuss the corresponding categories in which current methods and associated algorithms for car-like vehicle autonomous navigation belong. They are used especially for outdoor activities and they have to be able to account for the constraints imposed by the non-holonomic type of movement allowable for car-like mobile robots. In addition, we present a number of projects from various application areas in the industry that are using these technologies. Our review starts with a description of a very popular and successful family of algorithms, namely the Rapidly-exploring Random Tree (RRT) planning method. After discussing the great variety and modifications proposed for the basic RRT algorithm, we turn our focus to versions which can address highly dynamic environments, especially those which become increasingly uncertain due to limited accuracy of the sensors used. We, subsequently, explore methods which use Fuzzy Logic to address the uncertainty and methods which consider navigation solutions within the holistic approach of a Simultaneous Localization and Mapping (SLAM) framework. Finally, we conclude with some remarks and thoughts about the current state of research and possible future developments.
  • Radu, P. et al. (2013). A Multi-algorithmic Colour Iris Recognition System. in: Soft Computing Applications Proceedings of the 5th International Workshop Soft Computing Applications (SOFA). Berlin, Germany: Springer, pp. 45-56. Available at: http://dx.doi.org/10.1007/978-3-642-33941-7_7.
    The reported accuracies of iris recognition systems are generally higher on near infrared images than on colour RGB images. To increase a colour iris recognition system’s performance, a possible solution is a multialgorithmic approach with an appropriate fusion mechanism. In the present work, this approach is investigated by fusing three algorithms at the score level to enhance the performance of a colour iris recognition system. The contribution of this paper consists of proposing 2 novel feature extraction methods for colour iris images, one based on a 3-bit encoder of the 8 neighborhood and the other one based on gray level co-occurrence matrix. The third algorithm employed uses the classical Gabor filters and phase encoding for feature extraction. A weighted average is used as a matching score fusion. The efficiency of the proposed iris recognition system is demonstrated on UBIRISv1 dataset.
  • Howells, G. and Sirlantzis, K. (2010). A Proposal for Integrating Formal Logic and Artificial Neural Systems: A Practical Exploration. in: Ao, S. -I. and Gelman, L. eds. Electronic Engineering and Computing Technology. Netherlands: Springer, pp. 297-308. Available at: http://doi.dx.org/10.1007/978-90-481-8776-8_26.

Conference or workshop item

  • Canoz, V. et al. (2017). Embedded hardware for closing the gap between research and industry in the assistive powered wheelchair market. in: IEEE/SICE International Symposium on System Integration (SII 2016). IEEE. Available at: https://doi.org/10.1109/SII.2016.7843983.
    Literature is abound with smart wheelchair platforms of various developments, yet to date there has been little technology find its way to the market place. Many trials and much research has taken place over the last few decades however the end user has benefited precious little. There exists two fundamental difficulties when developing a smart powered wheelchair assistive system, the first is need for the system to be fully compatible with all of the manufacturers, and the second is to produce a technology and business model which is marketable and therefore desirable to the manufacturers. However this requires the researchers to have access to hardware which can be used to develop practical systems which integrate and communicate seamlessly with current manufacturer’s wheelchair systems. We present our powered wheelchair system which integrates with 95% of the powered wheelchair controller market; our system allows researchers to access the low level embedded system with more powerful computational devices running sophisticated software enabling rapid development of algorithms and techniques. When they have been evaluated they can be easily ported to the embedded processor for real-time evaluation and clinical trial.
  • Chatzidimitriadis, S. et al. (2017). Evaluation of 3D obstacle avoidance algorithm for smart powered wheelchairs. in: Seventh International Conference on Emerging Security Technologies (EST). IEEE, pp. 157-162. Available at: https://doi.org/10.1109/EST.2017.8090416.
    This research investigates the feasibility for the development of a novel 3D collision avoidance system for smart powered wheelchairs operating in a cluttered setting by using a scenario generated in a simulated environment using the Robot Operating System development framework. We constructed an innovative interface with a commercially available powered wheelchair system in order to extract joystick data to provide the input for interacting with the simulation. By integrating with a standard PWC control system the user can operate the PWC joystick with the model responding in real-time. The wheelchair model was equipped with a Kinect depth sensor segmented into three layers, two representing the upper body and torso, and a third layer fused with a LIDAR for the leg section. When using the assisted driving algorithm there was a 91.7% reduction in collisions and the course completion rate was 100% compared to 87.5% when not using the algorithm.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2016). A study on iris textural correlation using steering kernels. in: 8th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS 2016). IEEE. Available at: https://doi.org/10.1109/BTAS.2016.7791160.
    Research on iris recognition have observed that iris texture
    has inherent radial correlation. However, currently,
    there lacks a deeper insight into iris textural correlation.
    Few research focus on a quantitative and comprehensive
    analysis on this correlation. In this paper, we perform a
    quantitative analysis on iris textural correlation. We employ
    steering kernels to model the textural correlation in images.
    We conduct experiments on three benchmark datasets covering
    iris captures with varying quality. We find that the
    local textural correlation varies due to local characteristics
    in iris images, while the general trend of textural correlation
    goes along the radial direction. Moreover, we demonstrate
    that the information on iris textural correlation can
    be utilized to improve iris recognition. We employ this information
    to produce iris codes. We show that the iris code
    with the information on textural correlation achieves an improved
    performance compared to traditional iris codes.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2015). Exploiting stable and discriminative iris weight map for iris recognition under less constrained environment. in: 7th IEEE International Conference on Biometrics: Theory, Applications and Systems.
  • Hu, Y. et al. (2015). An online background subtraction algorithm using contiguously weighted linear regression. in: EUSIPCO 2015 - European Signal Processing Conference.. Available at: http://www.eusipco2015.org/.
  • Khemmar, R. et al. (2015). V2G-based Smart Autonomous Vehicle For Urban Mobility using Renewable Energy. in: SMART 2015 the Fourth International Conference on Smart Systems, Devices and Technologies : URBAN COMPUTING 2015, the International Symposium on Emerging Frontiers of Urban Computing. Brussels, Belgium, pp. 62-68.
    IRSEEM is coordinator of a research program Savemore [19] aiming to develop and demonstrate the viability and effectiveness of systems for electrical transport and urban logistics based on autonomous robotic electric vehicles operating within a smart grid electrical power distribution framework. As a part of this project, our work focuses on the study of the coupling of electric vehicles with renewable energy. At the scale of a city, electric vehicles can be considered as a means of intermittent storage of electric power which can be distributed to the network when it is required (e.g., at times of the date when demand spikes). When these vehicles belong to a controlled and intelligent fleet, network organization is dynamic and leads to a smart grid. The widespread use of electric vehicles in cities coupled with renewable energy appears as a powerful tool to help local and regional authorities in the implementation of the European Agenda for low-carbon, reduced air pollution and encourage energy savings. In this paper, we present a Vehicle to Grid model which implements the interaction between an electric vehicle and a smart grid. The model takes into account several kinds of parameters related to the battery, the charging station, the size of the fleet and the power grid as the expansion coefficient. A statistical approach is adopted for the setting of these parameters to determine the significant parameters. Several simulations are performed to validate the model. In first step, we have studied the behavior of the model on a typical day of a person who has traveled from his home to work (in France). As a second step, and in order to study the power consumption behavior of the model, we have tested it during several seasons. The results show the effectiveness of the model developed.
  • Spanogianopoulos, S. and Sirlantzis, K. (2015). Non-holonomic Path Planning of Car-like Robot using RRT*FN. in: 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI 2015). IEEE, pp. 53-57. Available at: http://dx.doi.org/10.1109/URAI.2015.7358927.
    Path planning of car-like robots can be done
    using RRT and RRT*. Instead of generating the non-
    holonomic path between two sampled configurations in
    RRT, our approach finds a
    small incremental step
    the next configuration. Since the incremental step can
    be in any direction we use RRT to guide the robot from
    start configuration to end configuration. Moreover, an
    effective variant of RRT called as RRT - Fixed Nodes
    (RRT*FN) is used to show the path planning of non-
    holonomic car-like robot. The algorithm is further tested
    with different static environments. The results show that
    RRT*FN implemented with non-holonomic constraints is
    able to find a feasible solution with the increased cost of
    number of iterations of RRT*FN while maintaining fixed
    number of nodes.
  • Ragot, N. et al. (2015). COALAS : A EU multidisciplinary research project for assistive robotics neuro-rehabilitation'. in: IEEE/RSJ International Conference on Intelligent Robots (IROS).
  • Motoc, I. et al. (2014). Zero Moment Point/Inverted Pendulum-Based Walking Algorithm for the NAO Robot. in: 2014 Fifth International Conference on Emerging Security Technologies (EST),. IEEE, pp. 63-66. Available at: http://doi.org/10.1109/EST.2014.34.
    Bipedal walking may be a difficult task to execute by a bipedal robot. Different factors such as the arm movement or the constant changing of the Center of Mass may lead to an unstable gait. This may be one of the reasons the trajectory of the Center of Mass should be calculated before making the next step. This paper presents a walking algorithm based on Zero Moment Point for the NAO robot. NAO is a 58 cm tall humanoid bipedal robot produced by the French company Aldebaran Robotics. Bipedal walking can be a quite difficult task, since the Center of Mass moves from one foot to another during the walking. For the NAO robot, walking is an even more difficult task, due to its limitations. This paper uses a Zero Moment Point-based walking algorithm in order to calculate the trajectory of the Center of Mass and obtain a stable and robust walk for NAO. The algorithm was used on a simulated environment using the NAO robot.
  • Motoc, I. et al. (2014). A Stable and Robust Walking Algorithm for the Humanoid Robot NAO based on the Zero Moment Point. in: CareTECH.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2014). A Robust Algorithm for Colour Iris Segmentation Based on 1-norm Regression. in: International Joint Conference on Biometrics.
  • Catley, E. et al. (2014). Non-overlapping dual camera fall detection using the NAO humanoid robot. in: 5th International Conference on Emerging Security Technologies. pp. 67-70.
    With an aging population and a greater desire for independence, the dangers of falling incidents in the elderly have become particularly pronounced. In light of this, several technologies have been developed with the aim of preventing or monitoring falls. Failing to strike the balance between several factors including reliability, complexity and invasion of privacy has seen prohibitive in the uptake of these systems. Some systems rely on cameras being mounted in all rooms of a user's home while others require being worn 24 hours a day. This paper explores a system using a humanoid NAO robot with dual vertically mounted cameras to perform the task of fall detection.
  • Spanogianopoulos, S. et al. (2014). Human computer interaction using gestures for mobile devices and serious games: A review. in: 2014 International Conference on Interactive Mobile Communication Technologies and Learning (IMCL),. IEEE, pp. 310-314. Available at: http://doi.org/10.1109/IMCTL.2014.7011154.
    The Human-Computer Interaction (HCI) with interfaces is an active challenge field in the industry over the past decades and has opened the way to communicate with the means of verbal, hand and body gestures using the latest technologies for a variety of different applications in areas such as video games, training and simulation. However, accurate recognition of gestures is still a challenge. In this paper, we review the basic principles and current methodologies used for collecting the raw gesture data from the user for recognize actions the users perform and the technologies currently used for gesture-HCI in games enterprise. In addition, we present a set of projects from various applications in games industry that are using gestural interaction.
  • Catley, E. et al. (2014). Preliminary investigations into human fall verification in static images using the NAO humanoid robot. in: CareTECH.
  • Radu, P. et al. (2013). A Novel Iris Clustering Approach Using LAB Color Features. in: 4th IEEE International Symposium on Electrical And Electronics Engineering (ISEEE 2013). IEEE, pp. 1-4. Available at: http://dx.doi.org/10.1109/ISEEE.2013.6674362.
    Interesting results of color clustering for the iris images in the UBIRISv1 database are presented. The iris colors are characterized by feature vectors with 80 components corresponding to histogram bins computed in the CIELAB color space. The feature extraction is applied to the first session eye images after undergoing an iris segmentation process. An agglomerative hierarchical algorithm is used to organize 1.205 segmented iris images in 8 clusters based on their color content.
  • Guness, S. et al. (2013). A Novel Depth-based Head Tracking and Gesture Recognition System. in: 12th European AAATE (Association for the Advancement of Assistive Technology in Europe) Conference. IOS Press EBooks, pp. 1021-1026. Available at: http://dx.doi.org/10.3233/978-1-61499-304-9-1021.
    This paper presents the architecture for a novel RGB-D based assistive device that incorporates depth as well as RGB data to enhance head tracking and facial gesture based control for severely disabled users. Using depth information it is possible to remove background clutter and therefore achieve a more accurate and robust performance. The system is compared with the CameraMouse, SmartNav and our previous 2D head tracking system. For the RGB-D system, the effective throughput of dwell clicking increased by a third (from 0.21 to 0.30 bits per second) and that of blink clicking doubled (from 0.15 to 0.28 bits per second) compared to the 2D system.
  • Ragot, N. et al. (2013). Enhancing the Autonomy of Disabled Persons: Assistive Technologies Directed by User Feedback. in: 4th International Conference on Emerging Security Technologies (EST 2013),. IEEE, pp. 71-74. Available at: http://dx.doi.org/10.1109/EST.2013.20.
    Europe faces a major and growing healthcare problem due to increase in population, increasing longevity and an aging population with disability. Such dependent, elderly, disabled and vulnerable persons, are concerned since they wish to live at home as long as possible. This aspiration is also shared by national policies and communities across EU. To ensure the optimum care of dependent people, innovative solutions are encouraged to maintain independent life style. This paper outlines two projects, SYSIASS and COALAS, which aim to develop a set of technology based solutions to meet the needs and empower these people by enhancing mobility and communication.
  • Gherman, B. and Sirlantzis, K. (2013). Polynomial Order Prediction Using a Classifier Trained on Meta-Measurements. in: 4th International Conference on Emerging Security Technologies, IEEE Conference. pp. 117-120. Available at: http://dx.doi.org/10.1109/EST.2013.26.
    Polynomial regression is still widely used in engineering and economics where polynomials of low order (usually less than tenth order) are being fitted to experimental data. However, the fundamental problem of selecting the optimal order of the polynomial to be fitted to experimental data is not a straightforward problem. This paper investigates the performance of automated methods for predicting the order of the polynomial that can be fitted on the decision boundary formed between two classes in a pattern recognition problem. We have investigated statistical methods and proposed a method of predicting the order of the polynomial. Our proposed machine learning method is computing a number of measurements on the input data which are used by a classifier trained offline to predict the order of the polynomial that should be fitted to the decision boundary. We have considered two matching scenarios. One scenario is where we have counted only the exact matches as being correct and another scenario in which we count as correct an exact match and higher polynomial orders. Experimental results on synthetic data show that our proposed method predicts the exact order of the polynomial with 31.90% accuracy as opposed to 13.22% of the best statistical method, but it also under-estimates the true order almost twice as often when compared to statistical methods of predicting the order of the polynomial to be fitted to the same data points.
  • Radu, P. et al. (2013). Optimizing 2D Gabor Filters for Iris Recognition. in: 4th International Conference on Emerging Security Technologies (EST 2013),. IEEE, pp. 47-50. Available at: http://dx.doi.org/10.1109/EST.2013.15.
    The randomness and richness present in the iris texture make the 2D Gabor filter bank analysis a suitable technique to be used for iris recognition systems. To accurately characterize complex texture structures using 2D Gabor filters it is necessary to use multiple sets of parameters of this type of filters. This paper proposes a technique of optimizing multiple sets of 2D Gabor filter parameters to gradually enhance the accuracy of an iris recognition system. The proposed methodology is suitable to be applied on both near infrared and visible spectrum iris images. To illustrate the efficiency of the filter bank design technique, UBIRISv1 database was used for benchmarking
  • Radu, P. et al. (2012). A Visible Light Iris Recognition System using Colour Information. in: 9th IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA 2012). Acta Press. Available at: http://dx.doi.org/10.2316/P.2012.778-019.
    The iris has been shown to be a highly reliable biometric modality with almost perfect authentication accuracy. However, a classical iris recognition system operates under near infrared illumination, which is a major constraint for a range of applications. In this paper, we propose an iris recognition system which is able to cope with noisy colour iris images by employing image processing techniques together with a Multiple Classifier System to fuse the information from various colour channels. There are two main contributions in the present work: first, we adapt standard iris features, proposed in the literature for near infrared images, to match the characteristics of colour iris images; second, we introduce a robust fusion mechanism to combine the features from various colour channels. With a feature size of only 360 real numbers, the efficiency of the proposed biometric system is demonstrated on the UBIRISv1 dataset for both identification and verification scenarios.
  • Guness, S. et al. (2012). Evaluation of vision-based head-trackers for assistive devices. in: 34th Annual International Conference of the IEEE EMBS. pp. 4804-4807. Available at: http://dx.doi.org/10.1109/EMBC.2012.6347068.
    This paper presents a new evaluation methodology for assistive devices employing head-tracking systems based on an adaptation of the Fitts Test. This methodology is used to compare the effectiveness and performance of a new vision-based head tracking system using face, skin and motion detection techniques with two existing head tracking devices and a standard mouse. The application context and the abilities of the user are combined with the results from the modified Fitts Test to help determine the most appropriate devices for the user. The results suggest that this modified form of the Fitts test can be effectively employed for the comparison of different access technologies.
  • McConnon, G. et al. (2012). Impact of common ophthalmic disorders on iris segmentation. in: Biometrics (ICB), 2012 5th IAPR International Conference. IEEE, pp. 277-282. Available at: http://dx.doi.org/10.1109/ICB.2012.6199820.
    As iris recognition moves from constrained indoor and near-infrared systems towards unconstrained on-the-move and at-a-distance systems, possibly using visible light illumination, interest in measurement of the fidelity of the acquired images and their impact on recognition performance has grown. However, the impact of the subject's physiological characteristics on the nature of the acquired images has received little attention. In this paper we catalog a selection of the most common ophthalmic disorders and investigate some of their characteristics including their prevalence and possible impact on recognition performance. The paper also includes an experimental exploration of the effect of such conditions on segmentation of the iris image.
  • Guness, S. et al. (2012). Developing a vision based gesture recognition system to control assistive technology in neuro-disability. in: 2012 Annual Conference, American Congress of Rehabilitation Medicine (2012 ACRM-ASNR). Elsevier Science B.V., p. e1. Available at: http://dx.doi.org/doi:10.1016/j.apmr.2012.08.202.
  • Radu, P. et al. (2012). Image Enhancement vs Feature Fusion in Colour Iris Recognition. in: Emerging Security Technologies (EST), 2012 Third International Conference. IEEE, pp. 53-57. Available at: http://dx.doi.org/10.1109/EST.2012.33.
    In iris recognition, most of the research was conducted on operation under near infrared illumination. For an iris recognition system to be deployed on common hardware devices, such as laptops or mobile phones, its ability of working with visible spectrum iris images is necessary. Two of the main possible approaches to cope with noisy images in a colour iris recognition system are either to apply image enhancement techniques or to extract multiple types of features and subsequently to employ an efficient fusion mechanism. The contribution of the present paper consists of comparing which of the two above mentioned approaches is best in both identification and verification scenarios of a colour iris recognition system. The efficiency of the two approaches is demonstrated on UBIRISv1 dataset
  • Radu, P. et al. (2011). Information Fusion for Unconstrained Iris Recognition. in: International Conference on Emerging Security Technologies (EST 2011).
  • Radu, P. et al. (2011). A Versatile Iris Segmentation Algorithm. in: 2011 BIOSIG Conference on Biometrics and Security.
  • Radu, P. et al. (2010). Are Two Eyes Better Than One? in: International Conference on Emerging Security Technologies (EST 2010).
  • McConnon, G. et al. (2010). A Novel Interactive Biometric Passport Photograph Alignment System. in: 18th European Symposium on Artificial Neural Networks (ESANN).
  • Sirlantzis, K. et al. (2010). Nomad Biometric Authentificatin (NOBA): Towards Mobile and Ubiquitous Person Identification. in: International Conference on Emergy Security Technologies (EST 2010).
  • McConnon, G. et al. (2010). A Survey of Point-Source Specular Reflections in Noisy Iris Images. in: Emerging Security Technologies (EST), 2010 International Conference. pp. 13-17. Available at: http://dx.doi.org/10.1109/EST.2010.33.
    This paper presents an examination of a selection of images taken from the UBIRIS.v2 dataset to explore the characteristics of point-source reflections present in the images. These reflections were some of the most commonly found sources of noise in iris images acquired under visual wavelength light and clearly impact the accuracy of iris recognition systems. The spatial and intensity distributions of these reflections is studied and results are presented that can be used to model their behaviour. This information can be helpful for developing more accurate iris synthesis techniques and for the study of iris image focus assessment as well as developing better matching algorithms for iris recognition.
  • Revett, K., Deravi, F. and Sirlantzis, K. (2010). Biosignals for User Authentication: Towards Cognitive Biometrics. in: 2010 International Conference on Emerging Security Technologies.


  • Mohamed, E., Sirlantzis, K. and Howells, G. (2019). Application of Transfer Learning for Object Detection on Manually Collected Data. in: Intelligent Systems Conference (IntelliSys) 2019.. Available at: https://saiconference.com/IntelliSys.
    This paper investigates the usage of pre-trained deep learning neural networks for object detection on a manually collected dataset for real-life indoor objects. Availability of object-specific datasets is a great challenge and the unavoidable task of collecting, processing and annotating ground truth data is laborious and time-consuming. In this paper, two famous models (AlexNet and Vgg16) have been evaluated as feature extractors in a Faster R-CNN network. Network models have been trained end-to-end on the collected dataset. The study highlights the poor performance of state of art systems when dealing with small size objects. Modifying the detector design by redesigning systems’ anchor boxes might help to tackle this problem. Detector results on the proposed dataset have been collected and compared. In addition, limitations and future work have been discussed.
  • Mohamed, E. et al. (2019). Integrating ride dynamics measurements and user comfort assessment to smart robotic wheelchairs. in: 15th Conference on Global Challenges in Assistive Technology: Research, Policy & Practice.. Available at: https://aaate2019.eu/.
    Individuals relying on wheelchairs for mobility are subject to the risk of injury due to their exposure to whole-body vibrations for long periods of time as per ISO 2631-1. Our study evaluates the feasibility of integrating ride dynamics measurements (i.e. vertical accelerations) as expressions of user travel comfort assessment to smart robotic wheelchairs. This will also help to mitigate the injury risk caused by the continuous exposure to vibrations using real time electronic measurement systems in order to ensure that the wheelchair’s movement dynamics (acceleration and speed) and the user’s comfort is adapted to the surrounding environment, specifically the type of ground surface type, as per the ISO standard mentioned previously.
  • Oprea, P. et al. (2019). Artificial intelligence for safe assisted driving based on user head movements in robotic wheelchairs. in: 15th Conference on Global Challenges in Assistive Technology: Research, Policy & Practice.. Available at: https://aaate2019.eu/.
    Wheelchairs users don’t always have the ability to control a powered wheelchair using a normal joystick due to factors that restrict the use of their arms and hands. For a certain number of these individuals, which still retain mobility of their head, alternative methods have been devised, such as chin-joysticks, head switches or sip-and-puff control. Such solutions can be bulky, cumbersome, unintuitive or simply uncomfortable and taxing for the user. This work presents an alternative head-based drive-control system for wheelchair users.
  • Motoc, I., Sirlantzis, K. and Spurgeon, S. (2016). A novel robust arm movement algorithm for humanoid robots based on finite time control. Journal of Intelligent & Robotic Systems.
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