Konstantinos Moustakas

• PhD
• Professor at University of Patras

This work presents a mixed reality (MR) system designed to explore inaccessible cultural heritage sites through immersive and interactive experiences. The application features two versions: an asynchronous personalized guided system offering interactions tailored to individual users’ requests and a synchronous guided system providing a shared, coll...

Fatigue modeling is essential for motion synthesis tasks to model human motions under fatigued conditions and biomechanical engineering applications, such as investigating the variations in movement patterns and posture due to fatigue, defining injury risk mitigation and prevention strategies, formulating fatigue minimization schemes and creating i...

Time‐varying meshes (TVMs), that is mesh sequences with varying connectivity, are a greatly versatile representation of shapes evolving in time, as they allow a surface topology to change or details to appear or disappear at any time during the sequence. This, however, comes at the cost of large storage size. Since 2003, there have been attempts to...

Artificial intelligence, machine learning, and deep learning as a service have become the status quo for many industries, leading to the widespread deployment of models that handle sensitive data. Well-performing models, the industry seeks, usually rely on a large volume of training data. However, the use of such data raises serious privacy concern...

Cyber–physical systems (CPSs) are evolving from individual systems to collectives of systems that collaborate to achieve highly complex goals, realizing a cyber–physical system of systems (CPSoSs) approach. They are heterogeneous systems comprising various autonomous CPSs, each with unique performance capabilities, priorities, and pursued goals. In...

In this paper we study the problem of shape part retrieval in the point cloud domain. Shape retrieval methods in the literature rely on the presence of an existing query object, but what if the part we are looking for is not available? We present Part Retrieval Pipeline (PReP), a pipeline that creatively utilizes metric learning techniques along wi...

We propose a novel point cloud U-Net diffusion architecture for 3D generative modeling capable of generating high-quality and diverse 3D shapes while maintaining fast generation times. Our network employs a dual-branch architecture, combining the high-resolution representations of points with the computational efficiency of sparse voxels. Our faste...

This paper introduces an innovative educational virtual reality (VR) experience aimed at immersing users in the complexities of spherical geometry. Focused on spherical triangles, navigation methods, and map projections, the VR journey offers an interactive platform for learning about Earth's unique geometry. Users engage in modules that explore th...

We present novel methods designed to elevate the realism of augmented reality (AR) applications focusing specifically on optical see-through devices. Our work integrates shadow rendering methods for multiple light sources and dynamic occlusion culling techniques. By creating custom surface shaders we can manage multiple light sources in real-time,...

One of the most common knee injuries is the Anterior Cruciate Ligament (ACL) rupture with severe implications on knee stability. The usual treatment is the ACL Reconstruction (ACLR) surgery where the surgeon replaces the torn ligament with a graft in an effort to restore knee kinematics. In case of excessive rotatory instability, Lateral Extra—Arti...

In this paper we delve into the properties of transformers, attained through self-supervision, in the point cloud domain. Specifically, we evaluate the effectiveness of Masked Autoencoding as a pretraining scheme, and explore Momentum Contrast as an alternative. In our study we investigate the impact of data quantity on the learned features, and un...

Most recent musculoskeletal dynamics estimation methods are designed for predefined actions, such as gait, and don’t generalize to various tasks. In this work, we address the problem of estimating internal biomechanical forces during more than one actions by introducing unsupervised domain adaptation into a deep learning model. More specifically, w...

Our objective is to design a highly innovative system, based on Artificial Intelligence (AI) processing and Augmented Reality (AR) rendering that will analyze both internal (sensing of ego-vehicle, in-cabin) and external (data from other connected vehicles) sources. The system will create Digital Twins and then provide drivers with personalized, no...

Autonomous vehicles are expected to operate safely in real-life road conditions in the next years. Nevertheless, unanticipated events such as the existence of unexpected objects in the range of the road, can put safety at risk. The advancement of sensing and communication technologies and Internet of Things may facilitate the recognition of hazardo...

One of the most common knee injuries is the Anterior Cruciate Ligament (ACL) rupture with severe implications on knee stability. The usual treatment is the ACL Reconstruction (ACLR) surgery where the surgeon replaces the torn ligament with a graft in an effort to restore knee kinematics. In case of excessive rotatory instability, Lateral Extra - Ar...

The inference of 3D motion and dynamics of the human musculoskeletal system has traditionally been solved using physics-based methods that exploit physical parameters to provide realistic simulations. Yet, such methods suffer from computational complexity and reduced stability, hindering their use in computer graphics applications that require real...

The automation of manufacturing applications where humans and robots operate in a shared environment imposes new challenges for presenting the operator’s safety and robot’s efficiency. Common solutions relying on isolating the robots’ workspace from human access during their operation are not applicable for HRI. This paper presents an extended real...

The increasing demand for accurate representations of 3D scenes, combined with immersive technologies has led point clouds to extensive popularity. However, quality point clouds require a large amount of data and therefore the need for compression methods is imperative. In this paper, we present a novel, geometry-based, end-to-end compression schem...

Thermal imaging is a widely used technique in several real-world applications in which a clear view of an object or scene is required, and obstruction thereof cannot be tolerated. By visualizing the received thermal radiation in the infrared spectrum, a clear depiction of the thermal profile of objects is obtained, that is information-rich and inva...

In this paper we delve into the properties of transformers, attained through self-supervision, in the point cloud domain. Specifically, we evaluate the effectiveness of Masked Autoencoding as a pretraining scheme, and explore Momentum Contrast as an alternative. In our study we investigate the impact of data quantity on the learned features, and un...

In this paper, the problem of lidar super-resolution is explored under a federated learning perspective. The high cost of high-resolution lidar sensors is a major obstacle to the widespread adoption of connected and autonomous vehicles (CAVs). To reduce the cost, this study investigates the use of low-cost sensors in conjunction with super-resoluti...

In collaborative tasks where humans work alongside machines, the robot's movements and behaviour can have a significant impact on the operator's safety, health, and comfort. To address this issue, we present a multi-stereo camera system that continuously monitors the operator's posture while they work with the robot. This system uses a novel distri...

The Anterior Cruciate Ligament (ACL) rupture is a very common knee injury during sport activities. Landing after jump is one of the most prominent human body movements that can lead to such an injury. The landing-related ACL injury risk factors have been in the spotlight of research interest. Over the years, researchers and clinicians acquire knowl...

Metabolic syndrome is a disorder that affects the overall function of the human body. It is manifested by elevated levels of cholesterol and triglycerides, a significant reduction in energy levels, weight gain with visceral fat deposition in the abdomen, and menstrual disorders while increasing the risk of cardiovascular disease, autoimmune disease...

Autonomous vehicles are expected to operate safely in real-life road conditions in the next years. Nevertheless, unanticipated events such as the existence of unexpected objects in the range of the road, can put safety at risk. The advancement of sensing and communication technologies and Internet of Things may facilitate the recognition of hazardo...

Asthma is a common, usually long-term respiratory disease with negative impact on global society and economy. Treatment involves using medical devices (inhalers) that distribute medication to the airways and its efficiency depends on the precision of the inhalation technique. There is a clinical need for objective methods to assess the inhalation t...

Hypertension is a chronic condition characterized by high pressure in the arteries of the human body. As a result, the heart is forced to work more intensively for the normal circulation of blood in the body. It is one of the most important risk factors for future fatal and non-cardiovascular diseases, stroke and kidney failure. In this article, Ma...

Nowadays, 3D meshes are widely used in various applications in different areas (e.g., industry, education, entertainment and safety). 3D models are captured with multiple RGB-D sensors, and the sampled geometric manifolds are processed, compressed, simplified, stored, and transmitted to be reconstructed in a virtual space. These low-level processin...

This paper presents a novel semantic data integration framework for monitoring and safeguarding the ergonomics of human operators during a collaborative assembly task in an automotive manufacturing environment.KeywordsSemantic data integrationOntologiesKnowledge graphsAutomotive manufacturing

Sleep is a vital component of human physical and mental health, but also a necessary condition for well-being and a better quality of life. In the work environment, sleep has an impact on employee productivity, workability, mental health and performance. This research work aims to combine applied methods of the GATEKEEPER 1 and SmartWork 2 projects...

This paper presents the methods that have participated in the SHREC 2022 track on the fitting and recognition of simple geometric primitives on point clouds. As simple primitives we mean the classical surface primitives derived from constructive solid geometry, i.e., planes, spheres, cylinders, cones and tori. The aim of the track is to evaluate th...

Throughout history, people have migrated from one place to another. People try to reach European shores for different reasons and through different channels. The “European migration crisis” is still ongoing and more than 34,000 migrants and refugees have died trying to get to Europe since 1993. Migrants look for legal ways, but also risk their live...

Chronic Obstructive Pulmonary Disease (COPD) is a disease characterized by persistent symptoms mainly in the respiratory system and permanent restriction of airflow. It can worsen over time and develop into a serious illness, being one of the leading causes of morbidity and mortality worldwide. In the context of this study, we focus on the early pr...

In this study, an exponentially weighted moving average (EWMA) filter is employed to transform the intensity values of RGB colour images. The processing is applied at the YCbCr colour system and targets only the component Y. The rationale behind the selection of temporal filtering with exponential weighting is to generate images with lower power si...

This paper presents the methods that have participated in the SHREC 2022 track on the fitting and recognition of simple geometric primitives on point clouds. As simple primitives we mean the classical surface primitives derived from constructive solid geometry, i.e., planes, spheres, cylinders, cones and tori. The aim of the track is to evaluate th...

Small animals stroke models have widely been used to study the mechanisms of ischemic brain damage in controllable experimental settings. The evaluation of stroke lesions mainly relies on visual inspection of tissue samples collected after brain sectioning, slice staining and scanning, a procedure that is highly subjective and prone to human error....

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...

Asthma is a common, usually long-term respiratory disease with negative impact on society and the economy worldwide. Treatment involves using medical devices (inhalers) that distribute medication to the airways, and its efficiency depends on the precision of the inhalation technique. Health monitoring systems equipped with sensors and embedded with...

Anterior cruciate ligament (ACL) tear is one of the most common knee injuries. The ACL reconstruction surgery aims to restore healthy knee function by replacing the injured ligament with a graft. Proper selection of the optimal surgery parameters is a complex task. To this end, we developed an automated modeling framework that accepts subject-speci...

Cardiovascular diseases (CVDs) are the leading cause of death worldwide and a major public health concern, with heart diseases being the most prevalent ones, thus the early prediction is being considered as one of the most effective measures for CVDs control. The risk evaluation for CVD occurrence on participants (men and women) especially aged old...

Cryo-electron tomography (cryo-ET) is an imaging technique that allows three-dimensional visualization of macro-molecular assemblies under near-native conditions. Cryo-ET comes with a number of challenges, mainly low signal-to-noise and inability to obtain images from all angles. Computational methods are key to analyze cryo-electron tomograms. To...

This paper presents multiple Virtual Reality 3D interaction, manipulation, and simulation techniques in the context of the 2022 3DUI contest of the IEEE VR conference. The proposed work provides the integration of 3DUI techniques and aims to familiarize and inform potential users about various artworks and artists. All techniques are implemented in...

An unbiased, automated and reliable method for analysis of brain lesions in tissue after ischemic stroke is missing. Manual infarct volumetry or by threshold-based semi-automated approaches is laborious, and biased to human error or biased by many false -positive and -negative data, respectively. Thereby, we developed a novel machine learning, atla...

Abnormal glucose metabolism increases the risk for cardiovascular disease and mortality. A key motivation for investigating this topic is Diabetes prevalence, which is the most common example of metabolic disorder that concern humans all over the world. The oral glucose tolerance test (OGTT) constitutes a traditional medical screening tool for all...

Optical Physical Unclonable Functions (PUFs) are well established as the most powerful anticounterfeiting tool. Despite the merits of optical PUFs, widespread use is hindered by existing implementations that are complicated and expensive. On top, the overwhelming majority of optical PUFs refer to extrinsic implementations. Here we overcome these li...

The technology of unmanned aerial vehicles (UAVs) has increasingly become part of many civil and research applications in recent years. UAVs offer high-quality aerial imaging and the ability to perform quick, flexible and in-depth data acquisition over an area of interest. While navigating in remote environments, UAVs need to be capable of autonomo...

The evolution of automotive technology will eventually permit the automated driving system on the vehicle to handle all circumstances. Human occupants will be just passengers. This poses security issues that need to be addressed. This paper has two aims. The first one investigates strategies for robustifying scene analysis of adversarial road scene...

Hypertension is a leading risk factor for cardiovascular diseases (CVDs) which in their turn are among the main causes of death worldwide and public health concern, with heart diseases being the most prevalent ones. The early prediction is considered one of the most effective ways for hypertension control. Based on the English Longitudinal Study of...

Virtual reality (VR) and 3D modeling technologies have become increasingly powerful tools for multiple fields, such as education, architecture, and cultural heritage. Museums are no longer places for only placing and exhibiting collections and artworks. They use such technologies to offer a new way of communicating art and history with their visito...

Recent advances in 3D scanning technology have enabled the deployment of 3D models in various industrial applications like digital twins, remote inspection and reverse engineering. Despite their evolving performance, 3D scanners, still introduce noise and artifacts in the acquired dense models. In this work, we propose a fast and robust denoising m...

3D representations of highly deformable 3D models, such as dynamic 3D meshes, have recently become very popular due to their wide applicability in various domains. This trend inevitably leads to a demand for storage and transmission of voluminous data sets, making the need for the design of a robust and reliable compression scheme a necessity. In t...

The acceptance of Automated Driving Systems is of key importance since it will determine whether they will actually be used. This presentation describes contributions in this broad area from the perspective of the Trustonomy project with a focus on ethical decision support, human machine interfaces and trust assessment, aimed at enhancing the exper...

Quality of life and wellness are heavily affected by sleep health, especially for older people who choose to remain active in the workforce. Workability and efficiency are correlated to sleep quality. Several non- automated sleep assessment tools have been used by professionals in the healthcare industry. These tools may rely on the user report of...

Cholesterol is a crucial risk factor for cardiovascular diseases (CVDs) which in their turn are among the main causes of death worldwide and public health concerns, with heart diseases being the most prevalent ones. For cholesterol control, early prediction is considered one of the most effective ways. Utilizing the English Longitudinal Study of Ag...

Synchronous office working environments are characterized by a high diversity of expertise and skills requirements during a product or service development. However, without the cooperation and optimal skills pairing among the employees, the success of a project may be negatively impacted. To take full advantage of the potential of each employee, pr...

3D representations of highly deformable 3D models, such as dynamic 3D meshes, have recently become very popular due to their wide applicability in various domains. This trend inevitably leads to a demand for storage and transmission of voluminous data sets, making the need for the design of a robust and reliable compression scheme a necessity. In t...

For individuals that already have been diagnosed with T2DM, accurate and timely prediction of blood glucose levels is critical to prevent hypoglycemic and hyperglycemic episodes. In clinical practice, continuous glucose monitoring (CGM) is used for the efficient management of glucose levels and, thus, diabetes. Several machine learning (ML) models...

A steady rise has been observed in the percentage of elderly people who want and are still able to contribute to society. Therefore, early retirement or exit from the labour market, due to healthrelated issues, poses a significant problem. Nowadays, thanks to technological advances and various data from different populations, the risk factors inves...

Cyber Physical Systems have been going into a transition phase from individual systems to a collecttives of systems that collaborate in order to achieve a highly complex cause, realizing a system of systems approach. The automotive domain has been making a transition to the system of system approach aiming to provide a series of emergent functional...

The rapid development of 3D acquisition devices enables us to collect billions of points in a few hours. However, the analysis of the output data is a challenging task, especially in the field of 3D point cloud change detection. In this Shape Retrieval Challenge (SHREC) track, we provide a street-scene dataset for 3D point cloud change detection. T...

Anterior Cruciate Ligament (ACL) tear is one of the most common knee injuries. The ACL reconstruction surgery aims to restore healthy knee function by replacing the injured ligament with a graft. Proper selection of the optimal surgery parameters is a complex task. To this end, we developed an automated modeling framework that accepts subject-speci...

The new generation 3D scanner devices have revolutionized the way information from 3D objects is acquired, making the process of scene capturing and digitization straightforward. However, the effectiveness and robustness of conventional algorithms for real scene analysis are usually deteriorated due to challenging conditions, such as noise, low res...

Achieving interactivity for applications with physically-accurate caustics is proven to be a challenging task. We present a hybrid method utilizing ray tracing and rasterization which enables water caustic coverage to vast view distance in real-time. Inspired by photon mapping, we optimize the generation of photons using cascaded caustic maps to av...

This paper presents the methods that have participated in the SHREC 2021 contest on retrieval and classification of protein surfaces on the basis of their geometry and physicochemical properties. The goal of the contest is to assess the capability of different computational approaches to identify different conformations of the same protein, or the...

This paper presents the methods that have participated in the SHREC 2021 contest on retrieval and classification of protein surfaces on the basis of their geometry and physicochemical properties. The goal of the contest is to assess the capability of different computational approaches to identify different conformations of the same protein, or the...

The main goal of the H2020-CARAMEL project is to address the cybersecurity gaps introduced by the new technological domains adopted by modern vehicles applying, among others, advanced Artificial Intelligence and Machine Learning techniques. As a result, CARAMEL enhances the protection against threats related to automated driving, smart charging of...

This study presents a semi-automatic framework to create subject-specific total knee replacement finite element models, which can be used to analyze locomotion patterns and evaluate knee dynamics. In recent years, much scientific attention was attracted to pre-clinical optimization of customized total knee replacement operations through computation...

The use of virtual reality (VR) techniques for industrial training provides a safe and cost effective solution that contributes to increased engagement and knowledge retention levels. However, the process of experiential learning in a virtual world without biophysical constraints might contribute to muscle strain and discomfort, if ergonomic risk f...

This study aims to explore the possibility of estimating a multitude of kinematic and dynamic quantities using subject-specific musculoskeletal models in real-time. The framework was designed to operate with marker-based and inertial measurement units enabling extensions far beyond dedicated motion capture laboratories. We present the technical det...

Simultaneous localization and mapping (SLAM) refers to the problem of mapping an environment using measurements from mobile sensors while simultaneously estimating the motion of those sensors relative to the map Modular architectures are required to enable the commoditization and fast penetration of SLAMs in the emerging mobile computing systems.

This paper presents Virtual Reality 3D interaction and simulation techniques in the context of the 2021 3DUI contest of the IEEE VR conference. This work discusses the design and development of a simulation based on COVID-19 indoor safety guidelines, aiming to familiarize and inform the potential users about the methods of transmission of SARS-CoV-...

This study aims to explore the possibility of estimating a multitude of kinematic and dynamic quantities using subject-specific musculoskeletal models in real-time. The framework was designed to operate with marker-based and inertial measurement units enabling extensions far beyond dedicated motion capture laboratories. We present the technical det...

This study aims to explore the possibility of estimating a multitude of kinematic and dynamic quantities using subject-specific musculoskeletal models in real-time. The framework was designed to operate with marker-based and inertial measurement units enabling extensions far beyond dedicated motion capture laboratories. We present the technical det...

The incorporation of a-priori knowledge on the shape of anatomical structures and their variation through Statistical Shape Models (SSMs) has shown to be very effective in guiding highly uncertain image segmentation problems. In this paper, we construct multiple-structure SSMs of purely geometric nature, that describe the relationship between adjac...