Dimitrios Giakoumis

The Centre for Research and Technology, Hellas

The importance of construction automation has grown worldwide, aiming to deliver new machineries for the automation of roads, tunnels, bridges, buildings and earth-work construction. This need is mainly driven by (i) the shortage and rising costs of skilled workers, (ii) the tremendous increased needs for new infrastructures to serve the daily acti...

Embodied virtual agents (EVAs) are increasingly used as means of communication with individuals in everyday life. However, first and foremost, these artificial intelligence technologies need to be trusted and liked if users are to widely adopt it. The utilization of implicit nonverbal cues, can play a key role in human-agent interaction by elicitin...

Due to the accelerated growth of the world’s population, food security and sustainable agricultural practices have become essential. The incorporation of Artificial Intelligence (AI)-enabled robotic systems in cultivation, especially in greenhouse environments, represents a promising solution, where the utilization of the confined infrastructure im...

The accurate and detailed 3D reconstruction of the construction sites plays a vital role in the digitalization of the construction domain, since accurate 3D models constitute the basis for the adaptation of advanced technologies from Industry 4.0 towards realizing Construction 4.0. This study provides a comprehensive assessment of key methodologies...

Autonomous vehicle navigation in complex and unpredictable outdoor environments requires extensive and detailed understanding of the surrounding area and compliance with the traffic rules. In this paper, we attempt to imitate human driver behavior towards autonomous navigation that is suitable for diverse, challenging environments, whether urban, s...

Computer vision is becoming increasingly important in agriculture, as it can provide important insights and lead to better informed decisions and reduce costs. However, working on the agriculture domain introduces important challenges, such as adverse conditions, small structures and lack of large datasets, hindering its wide adoption on multiple c...

Achieving a robust long‐term deployment with mobile robots in the agriculture domain is both a demanded and challenging task. The possibility to have autonomous platforms in the field performing repetitive tasks, such as monitoring or harvesting crops, collides with the difficulties posed by the always‐changing appearance of the environment due to...

A study conducted by the World Bank indicated that the global annual economic losses from the water leakage are estimated at US$ 14.6 billion. For this reason, locating and repairing water leaks as well as the maintenance of water pipelines is extremely important for the optimization and rationalization of water resources. The basic technique for i...

This paper presents a comprehensive review of ground agricultural robotic systems and applications with special focus on harvesting that span research and commercial products and results, as well as their enabling technologies. The majority of literature concerns the development of crop detection, field navigation via vision and their related chall...

The occurring growth in e-commerce comes along with an increasing number of first-time delivery failures due to the customer’s absence at the delivery location. Failed deliveries result in rework, causing a significant impact on the carriers’ delivery cost. Hence, the last mile is the portion of a journey that involves moving people and commodities...

This paper presents a comprehensive review of ground agricultural robotic systems and applications with special focus on harvesting that span research and commercial products and results, as well as their enabling technologies. The majority of literature concerns the development of crop detection, field navigation via vision and their related chall...

Automated inspection of energy infrastructure with Unmanned Aerial Vehicles (UAVs) is becoming increasingly important, exhibiting significant advantages over manual inspection, including improved scalability, cost/time effectiveness, and risks reduction. Although recent technological advancements enabled the collection of an abundance of vision dat...

Behavioral monitoring tools can be proven to be especially helpful for aging workers for whom it is of paramount importance to avoid sedentary lifestyle, decreasing the possibility to exhibit musculoskeletal, cardiovascular and other health/mental related problems, which could impede their workability and job performance. Towards this direction, we...

Aiming to address the needs of the ageing workforce in the context of shift work, we introduce a Participatory Work Orchestration Support Tool, with the aim of supporting decision making in deriving the periodic shift schedule of an organization. The proposed tool comprises two main components, an extensive and intuitive web-based platform that ena...

Modern augmented and virtual reality (AR/VR) technology open multiple new capabilities in the way people interact, collaborate and deliver or receive information via digital interfaces. Industry workers and operators may especially benefit from such solutions that allow them to get trained, onsite or remotely, using digital copies of the workplace...

This study conducted a preliminary usability assessment of the Virtual Supermarket Test (VST), a serious game-based self-administered cognitive screening test for mild cognitive impairment (MCI). Twenty-four healthy older adults with subjective cognitive decline and 33 patients with MCI self-administered the VST and then completed the System Usabil...

During the last few decades, great research endeavors have been applied to healthcare robots, aiming to develop companions that extend the independent living of elderly people. To deploy such robots into the market, it is expected that certain applications should be addressed with repeatability and robustness. Such application is the assistance wit...

Human Activity Recognition is a field that provides the fundamentals for Ambient Intelligence and Assisted Living Applications. Multimodal methods for Human Activity Recognition utilize different sensors and fuse them together to provide higher-accuracy results. These methods require data for all sensors employed to operate with. In this work we pr...

Sedentary behavior is considered as a major public health challenge, linked with many chronic diseases and premature mortality. In this paper, we propose a steps counting -based machine learning approach for the prediction of sedentary behavior. Our work focuses on analyzing historical data from multiple users of wearable physical activity trackers...

Many visual scene understanding applications, especially in visual servoing settings, may require high quality object mask predictions for the accurate undertaking of various robotic tasks. In this work we investigate a setting where separate instance labels for all objects under view are required, but the available instance segmentation methods pr...

Semantic mapping has received much attention in the recent years due to the fact that more and more robots need to operate in complex environments and co-exist with humans or other robots. This requires contemporary robots not only to be able to navigate safely in their environment, but also to adopt a human-like understanding of their surroundings...

Pervasive technologies such as Artificial Intelligence, Virtual Reality and the Internet of Things, despite their great potential for improved workability and well-being of older workers, entail wide ethical concerns. Aligned with these considerations we emphasize the need to present from the viewpoint of ethics the risks of personalized ICT soluti...

Remote working and collaboration is important towards helping workplaces to become flexible and productive. The significance of remote working has also been highlighted in the COVID-19 pandemic period in which mobility restrictions were enforced. This paper presents the development of an augmented reality platform, aiming to assist workers in remot...

The future civilian, and professional autonomous vehicles to be realised into the market should apprehend and interpret the road in a manner similar to the human drivers. In structured urban environments where signs, road lanes and markers are well defined and ordered, landmark-based road tracking and localisation has significantly progressed durin...

Background There is a need for new practical tools to assess the cognitive impairment of small vessel disease (SVD) patients in the clinic. Objective This study aimed to examine cognitive functioning by administering the Virtual Supermarket (VST) in patients with SVD with cognitive impairment (SVD-CI, N = 32), cognitively normal SVD (SVD-CN, N = 3...

Human-Robot Collaboration (HRC) in industry is a promising research direction that has potential to expand robotics to previously unthinkable application areas. Orchestration of large hybrid human-robot teams carrying out many tasks in parallel within a shop floor faces new challenges due to unique aspects introduced by HRC. This paper presents a n...

Background Detailed neuropsychological assessment is essential to detect cognitive impairment in SVD. Therefore, a brief cognitive test is needed as an alternative to extensive assessment (Peng et al., 2019). The aim of this study is to examine cognitive functions between SVD with cognitive impairment (SVD‐CI), cognitively normal SVD (SVD‐CN), and...

Background: Literature supports the use of serious games and virtual environments to assess cognitive functions and detect cognitive decline. This promising assessment method, however, has not yet been translated into self-administered screening instruments for pre-clinical dementia. Objective: The aim of this study is to assess the performance...

Environmental sound signals are multi-source, heterogeneous, and varying in time. Many systems have been proposed to process such signals for event detection in ambient assisted living applications. Typically, these systems use feature extraction, selection, and classification. However, despite major advances, several important questions remain una...

The use of Convolutional Neural Networks (CNNs) as a feature learning method for Human Activity Recognition (HAR) is becoming more and more common. Unlike conventional machine learning methods, which require domain-specific expertise, CNNs can extract features automatically. On the other hand, CNNs require a training phase, making them prone to the...

A novel affective policy has been developed for a service robot, which emphasizes on assistance scenarios focusing on the needs of persons with mild cognitive impairment (MCI) and at early Alzheimer’s disease (AD) stages, at home. This chapter introduces a theoretical framework whose main contribution is twofold; the first one concerns a study on d...

Structured space exploration with mobile robots is imperative for autonomous operation in challenging outdoor applications. To this end, robots should be equipped with global path planners that ensure coverage and full exploration of the operational area as well as dynamic local planners that address local obstacle avoidance. The paper at hand prop...

The recent development of novel powerful sensor topologies, namely Ground Penetrating Radar (GPR) antennas, gave a thrust to the modeling of underground environment. An important step towards underground modelling is the detection of the typical hyperbola patterns on 2D images (B-scans), formulated due to the reflections of underground utilities. T...

The purpose of this study was to investigate cognitive functioning by administering the Virtual Supermarket (VSM) test in patients with amnestic mild cognitive impairment (aMCI, N = 37) and age and education-matched healthy controls (HCs, N = 52). An extensive neuropsychological test battery and the VSM were administered to all participants. The aM...

Deep learning techniques such as Convolutional Neural Networks (CNNs) have shown good results in activity recognition. One of the advantages of using these methods resides in their ability to generate features automatically. This ability greatly simplifies the task of feature extraction that usually requires domain specific knowledge, especially wh...

Along with population ageing comes the increasingly intensified phenomenon of a shrinking and ageing workforce. Novel solutions are needed so as to help ageing workers maintain workability and productivity, along with a balance between work and personal life, which supports them into good quality of life, active and healthy ageing. In this line, th...

Personal assistive robots to be realized in the near future should have the ability to seamlessly coexist with humans in unconstrained environments, with the robot’s capability to understand and interpret the human behavior during human–robot cohabitation significantly contributing towards this end. Still, the understanding of human behavior throug...

Background: New technologies and especially computerized cognitive screening have been proposed as a means to increase access to timely cognitive screening. This Pilot Project assesses the effectiveness of an innovative self-screening test, the Virtual Supermarket Test (VST), and the Greek version of the UCSF Brain Health Assessment (BHA) that can...

At the last decades, personal domestic robots are considered as the future for tackling the societal challenge inherent in the growing elderly population. Ageing is typically associated with physical and cognitive decline, altering the way an older person moves around the house, manipulates objects and senses the home environment. This paper aims t...

This book constitutes the refereed proceedings of the 12th International Conference on Computer Vision Systems, ICVS 2019, held in Thessaloniki, Greece, in September 2019. The 72 papers presented were carefully reviewed and selected from 114 submissions. The papers are organized in the following topical sections; hardware accelerated and real time...

We propose a new approach to natural language understanding in which we consider the input text as an image and apply 2D Convolutional Neural Networks to learn the local and global semantics of the sentences from the variations ofthe visual patterns of words. Our approach demonstrates that it is possible to get semantically meaningful features from...

For a proactive and user-centered robotic assistance and communication, an assistive robot must make decisions about the level of assistance to be provided. Therefore, the robot must be aware of the preferences and the capabilities of the elderly. At the same time, relying on a sensing setup which is totally embedded in the assistive robot would in...

We propose a framework for energy-based human activity recognition in a household environment. We apply machine learning techniques to infer the state of household appliances from their energy consumption data and use rulebased scenarios that exploit these states to detect human activity. Our decision engine achieved a 99.1% accuracy for real-world...

This paper describes our contribution to the 2017 Detection and Classification of Acoustic Scenes and Events (DCASE) challenge. We investigated two approaches for the acoustic scene classification task. Firstly, we used a combination of features in the time and frequency domain and a hybrid Support Vector Machines - Hidden Markov Model (SVM-HMM) cl...

The incorporation of service robots in human populated environments gives rise to the adaptation of cruise strategies that allow robots to move in a natural, secure and ordinary manner among their cohabitants. Therefore, robots should firstly apprehend their space similarly with the people and, secondly, should adopt human motion anticipation strat...

Building an acoustic-based event recognition system for smart homes is a challenging task due to the lack of high-level structures in environmental sounds. In particular, the selection of effective features is still an open problem. We make an important step toward this goal by showing that the combination of Mel-Frequency Cepstral Coefficients, Ze...

This paper presents a novel approach for automatic human action recognition, focusing on user behaviour monitoring needs of assistive robots that aim to support Mild Cognitive Impairment (MCI) patients at home. Our action recognition method utilizes the human's skeleton joints information, extracted from a low-cost depth sensor mounted on a service...

This paper proposes a theoretical framework that determines the high-level cognitive functions for multipurpose assistive service robots, required to autonomously complete their tasks. It encompasses a probabilistic POMDP based decision-making strategy that provides constant situation awareness about the human and the environment by associating the...

Background: It has been demonstrated that virtual reality (VR) applications can be used for the detection of mild cognitive impairment (MCI). Objective: The aim of this study is to provide a preliminary investigation on whether a VR cognitive training application can be used to detect MCI in persons using the application at home without the help...

In the near future, the seamless human robot cohabitation can be achieved as long as the robots to be released in the market attain socially acceptable behavior. Therefore, robots need to learn and react appropriately, should they be able to share the same space with people and to adapt their operation to human’s activity. The goal of this work is...

This paper presents a framework that has been developed for automatic activity recognition and domestic behavior monitoring, towards supporting elderly MCI patients in their daily domestic life. Our framework's infrastructure consists of a network of smart-home sensors and RGB-D cameras that can be adapted and be unobtrusively installed in a variet...

The 2015 International Symposium on Pervasive Computing Paradigms for Mental Health – MindCare was held at the Istituto Auxologico Italiano, in Milan, Italy, during September 24–25, 2015. The symposium focused on the use of technologies in favor of maintaining and improving mental well-being and it brought together the community of researchers and...