George Alexis Ioannakis

• PhD
• Assistant Researcher at Athena Research and Innovation Center In Information Communication & Knowledge Technologies

A number of software solutions based on the Structure-From-Motion (SFM) and Dense Multi-View 3D Reconstruction (DMVR) algorithms have been made recently available. They allow the production of high quality 3D models by using unordered image collections that depict a scene or an object from different viewpoints. In this work, we question the quality...

One of the factors that determine the data quality produced by targetless photogrammetric techniques is the feature richness of the surface being captured. The Structure-From-Motion and Multiple View Stereovision (SFM-MVS) pipeline is no exception to this rule as it relies on the ability to identify corresponding points within a collection of unord...

The aim of this research is to achieve spatial consistency of the UV map. We present an approach to produce a fully spatially consistent UV mapping based on the planar parameterisation of the mesh. We apply our method on a 3D digital replica of an ancient Greek Lekythos vessel. We parameterise the mesh of a 3D model onto a unit square 2D plane usin...

Performance evaluation is one of the main research topics in information retrieval. Evaluation metrics are used to quantify various performance aspects of a retrieval method. These metrics assist in identifying the optimum method for a specific retrieval challenge but also to allow its parameters finetuning in order to achieve a robust operation fo...

The intersection of COVID-19 and pulmonary embolism (PE) has posed unprecedented challenges in medical diagnostics. The critical nature of PE and its increased incidence during the pandemic underline the need for improved detection methods. This study evaluates the effectiveness of advanced deep learning techniques in enhancing PE detection in post...

Water molecules are integral to the structural stability of proteins and vital for facilitating molecular interactions. However, accurately predicting their precise position around protein structures remains a significant challenge, making it a vibrant research area. In this paper, we introduce HydraProt (deep Hydration of Proteins), a novel method...

We introduce a new corpus, named AIKIA, for Offensive Language Detection (OLD) in Modern Greek (EL). EL is a less-resourced language regarding OLD. AIKIA offers free access to annotated data leveraged from EL Twitter and fiction texts using the lexicon of offensive terms, ERIS, that originates from HurtLex. AIKIA has been annotated for offensive va...

Haptic contact is usually prohibited when exploring cultural heritage content. This inevitably results in an incomplete experience for the visually impaired as tactile exploration is the dominant substitute of sight. In this paper, we focus on Information and Communication Technologies utilisation to enable cultural heritage content to become more...

Plant phenotyping refers to a quantitative description of the plant's properties, however in image-based phenotyping analysis, our focus is primarily on the plant's anatomical, ontogenetical and physiological properties. This technique reinforced by the success of Deep Learning in the field of image based analysis is applicable to a wide range of r...

Plant phenotyping refers to a quantitative description of the plants properties, however in image-based phenotyping analysis, our focus is primarily on the plants anatomical, ontogenetical and physiological properties.This technique reinforced by the success of Deep Learning in the field of image based analysis is applicable to a wide range of rese...

The sunken city of old Epidaurus is one of the most significant archaeological sea-sites on the east coast of Peloponnese, Greece. Remains of ancient buildings are preserved in the area with a Roman villa located about 50m from the coast, the most notable of them. The site is attracting tourists and researchers from various scientific domains, such...

Haptic prohibition is one of the most common limitations when interacting with museum artefacts. This restriction aims quite logically at preventing damages while safeguarding the integrity of the cultural reserve, which is primarily characterised by its uniqueness. Nevertheless, in cases where museum visitors are visually impaired, the inability t...

The main objective of this work is to utilize state-of-the-art deep learning approaches for the identification of pulmonary embolism in CTPA-Scans for COVID-19 patients, provide an initial assessment of their performance and, ultimately, provide a fast-track prototype solution (system). We adopted and assessed some of the most popular convolutional...

Disaster risk management of movable and immovable cultural heritage is a highly significant research topic. In this work, we present a pipeline for 3D digitisation, segmentation and annotation of large scale urban areas in order to produce data that can be exploited in disaster management simulators (e.g fire spreading, crowd movement, firefighting...

ESTIA is a research and innovation project that aspires to develop a comprehensive platform allowing the forecast, detection and management of incidents that are related with the risk of structural fires within Cultural Heritage (CH) settlements and sites. ESTIA aims to (a) enhance the management and preservation of CH, (b) limit the risks of fire...

One of the most challenging tasks in cross reality environment simulations is the generation of realistic and attractive worlds. The continuous evolution of computer game industry has a dramatic effect on such tasks as younger generations have higher expectations and demands in terms of realism. Virtual, Augmented, and mixed reality-based museums a...

Numerous software solutions implementing the structure-from-motion/multi-view stereo (SFM/MVS) 3D reconstruction approach have been made available over the last two decades. Hence, enabling the production of high quality, in terms of geometry and colour information, 3D objects using solely unordered image sequences depicting a static scene or objec...

The on-demand content enrichment of an exhibition center visit is an active applied research domain. This work focuses on the exploitation of mobile devices as an efficient medium to deliver information related to an exhibit or an area within the exhibition center by utilizing machine learning approaches. We present YPOPSEI, an integrated system th...

Machine learning is constantly proving its capabilities by achieving exceptional results in recognition and classification tasks. Image content recognition has been addressed by Bags of Visual Words coupled with a classification algorithm as well as convolutional neural networks. In this work, we question the applicability of these approaches indiv...

Performance evaluation is one of the main research topics in information retrieval. Evaluation metrics in combination with benchmark datasets (groundtruth) are used to quantify various performance aspects of a retrieval algorithm. In this paper, we present the Orion Pottery Repository, a publicly available and domain specific benchmark database. It...

Numerous software solutions that implement the Structure-from-Motion/Multi-View Stereo (SfM/MVS) 3D reconstruction approach have been made available during the last decade. These allow the production of high quality in terms of geometry and colour information 3D models with the use of unordered image collections that depict a static scene or object...

Despite numerous recent efforts, 3D object retrieval based on partial shape queries remains a challenging problem, far from being solved. The problem can be defined as: given a partial view of a shape as query, retrieve all partially similar 3D models from a repository. The objective of this track is to evaluate the performance of partial 3D object...

Performance benchmarking is an absolute necessity when attempting to objectively quantify the performance of content-based retrieval methods. For many years now, a number of plot-based and scalar-based measures in combination with benchmark datasets have already been used in order to provide objective results. In this work, we present the first ver...

The generation of 3D models with the Structure-from-Motion and Multiple View Stereovision (SFM-MVS) techniques is considered popular within the cultural heritage domain. The cost effectiveness in terms of hardware equipment and relatively low background knowledge requirements are two major SFM-MVS properties while the quality of the data produced c...

Web-based dissemination of cultural heritage 3D content has been vividly increased over the last decade. EU-funded research and development projects established affordable pipelines in order to allow efficient 3D documentation and dissemination. Such an example is the 3D-ICONS project that was focused on the 3D digitisation of outstanding cultural...

3D digitisation has been applied in different application domains. Due to the continuous growing interest, commercial and experimental 3D acquisition systems have evolved. Nevertheless, there isn't an all-in-one solution, thus there is a need for combining different technologies in order to exploit the advantages of each approach. In this paper, we...